FOOD SAFETY

FDA and USDA 

Should Strengthen 

Pesticide Residue 

Monitoring Programs 

and Further Disclose 

Monitoring Limitations

Report to the Ranking Member, 

Subcommittee on Environment and the 

Economy, Committee on Energy and 

Commerce, House of Representatives

October 2014

GAO-15-38

United States Government Accountability Office
United States Government Accountability Office

Highlights of GAO-15-38, a report to the 

Ranking Member, Subcommittee on 

Environment and the Economy, Committee on 

Energy and Commerce, House of 

Representatives

October 2014

FOOD SAFETY

FDA and USDA Should Strengthen Pesticide Residue 

Monitoring Programs and Further Disclose 

Monitoring Limitations

Why GAO Did This Study

From 1970 to 2007, hundreds of 

millions of pounds of pesticides were 

applied annually to U.S. food crops to 

protect them from pests. To protect 

consumers, EPA sets standards—

known as tolerances—for pesticide 

residues on foods. FSIS monitors 

meat, poultry, and processed egg 

products to ensure they do not violate 

EPA’s tolerances, and FDA monitors 

other foods, including fruits and 

vegetables. AMS gathers annual

residue data for highly consumed 

foods, although not for enforcement 

purposes. 

GAO was asked to review federal 

oversight of pesticide residues in food. 

This report examines (1) what FDA 

data show with respect to pesticide 

residue violations in the foods that it 

regulates; (2) what FSIS data show 

with respect to pesticide residue 

violations in the foods that it regulates; 

and (3) what AMS data show with 

respect to pesticide residue levels in 

fruits and vegetables. For each 

agency, GAO examined limitations, if 

any, in the agencies’ monitoring of 

foods for pesticide residues. GAO 

analyzed FDA, FSIS, and AMS 

pesticide residue data, including their 

reliability, reviewed agency methods 

for sampling foods for testing, and

interviewed agency officials. 

What GAO Recommends

GAO recommends that FDA improve 

its methodology and FDA and USDA

disclose limitations in their monitoring 

and data collection efforts. FDA said it 

will consider methodological changes 

and will disclose limitations. USDA 

agreed with GAO’s recommendations.

What GAO Found

The Food and Drug Administration’s (FDA) most recent data from 2008 through 

2012 show that pesticide residue violation rates in 10 selected fruits and 

vegetables were low, but FDA’s approach to monitoring for violations, which 

targets commodities it has identified as high risk, has limitations. Among other 

things, GAO found that FDA tests relatively few targeted (i.e., non-generalizable) 

samples for pesticide residues. For example, in 2012, FDA tested less than onetenth of 1 percent of imported shipments. Further, FDA does not disclose in its 

annual monitoring reports that it does not test for several commonly used 

pesticides with an Environmental Protection Agency (EPA) established tolerance

(the maximum amount of a pesticide residue that is allowed to remain on or in a 

food)—including glyphosate, the most used agricultural pesticide. Although FDA 

is not required by law to select particular commodities for sampling or test for 

specific pesticides, disclosing this limitation would help meet Office of 

Management and Budget (OMB) best practices for conducting and reporting data 

collection and help users of the reports interpret the data. Also, FDA does not 

use statistically valid methods consistent with OMB standards to collect national 

information on the incidence and level of pesticide residues. FDA officials said 

that it would be costly to calculate national estimates for the foods it regulates

because it would require a large number of samples for a wide array of products, 

but did not provide documentation on the cost of doing so or an assessment of

the trade-offs of doing less targeting and more random sampling. Limitations in 

FDA’s methodology hamper its ability to determine the national incidence and 

level of pesticide residues in the foods it regulates, one of its stated objectives. 

For domestic and imported meat, poultry, and processed egg products, the U.S. 

Department of Agriculture’s (USDA) Food Safety and Inspection Service’s (FSIS) 

most recent available data from 2000 through 2011 show the agency found a low 

rate of pesticide residue violations, but its data had limitations. Specifically, for 

this period, FSIS did not test meat, poultry, and processed egg products for all 

pesticides with established EPA tolerance levels. Like FDA, FSIS is not required 

by law to test the foods it samples for specific pesticides, but disclosing this 

limitation in annual reports would meet OMB reporting best practices. Since 

2011, FSIS has increased the number of pesticides it has tested for and samples 

it has taken and engaged with EPA on changes to FSIS’s monitoring program to 

better provide EPA with data it needs to assess the risks of pesticides. 

The most recent data from USDA’s Agricultural Marketing Service’s (AMS) 

annual survey of highly consumed commodities, including fruits and vegetables,

show that, from 1998 through 2012, pesticide residue detections varied by 

commodity and were generally well below tolerance levels. EPA and others 

praise AMS’s data collection efforts as providing valuable information on the 

incidence and level of pesticide residues in foods. In addition, while the sampling 

methodology used by AMS in the Pesticide Data Program meets many of OMB’s 

best practices for conducting and releasing information to the public concerning a 

data collection effort, it does not meet several others, such as some principles of 

probability sampling that are important for ensuring that the data the agency 

collects are nationally representative. As AMS does not disclose these limitations 

in its annual monitoring reports, users of the data may misinterpret information in 

these reports and draw erroneous conclusions based on the data.

View GAO-15-38. For more information, 

contact John Neumann at (202) 512-3841 or 

neumannj@gao.gov.
Page i GAO-15-38 Pesticide Residue Monitoring

Letter 1 

Background 5

FDA Data Show Low Rates of Pesticide Residue Violations, but 

FDA’s Approach for Detecting Violations Has Limitations That 

Are Not Disclosed 15

FSIS Data for 2000 through 2011 Show Low Pesticide Residue 

Violation Rates for Meat, Poultry, and Processed Egg Products, 

but FSIS Did Not Disclose Limitations in the Data 38

AMS’s Survey Data Show Pesticide Residues Vary by Commodity 

and Are Generally Well below Tolerance Levels, but Annual 

Reports Do Not Disclose Survey Limitations 48

Conclusions 55

Recommendations for Executive Action 57

Agency Comments and Our Evaluation 58

Appendix I Objectives, Scope, and Methodology 64

Appendix II Food and Drug Administration Pesticide Residue Monitoring Data 

for 10 Selected Commodities from 1993 through 2012 75

Appendix III Analysis of Pesticide Residues at Different Points in Time, Taking 

into Account Changes in Monitoring Methodologies and Pesticide 

Tolerances 86

Appendix IV Comments from the Department of Health and Human Services 96

Appendix V Comments from the U.S. Department of Agriculture 100

Appendix VI GAO Contact and Staff Acknowledgments 103

Contents
Page ii GAO-15-38 Pesticide Residue Monitoring

Related GAO Products 104

Tables

Table 1: Presumptive Tolerance Violation Rates for 10 Selected 

Commodities, Based on Agricultural Marketing Service 

(AMS) Data, Three Most Recent Years With Data 

Available for Each Commodity 21

Table 2: Imported Food Commodities Analyzed by FDA with a 

Violation Rate of 10 Percent or Higher, Fiscal Year 2011 22

Table 3: FDA’s Predictive Risk-based Evaluation for Dynamic 

Import Compliance Targeting (PREDICT) Scoring for 

Imported Food Entry Lines, Sampling Data, and Violation 

Rates in 2012 31

Table 4: Pesticides with Tolerances for Direct Use on Food

Animals in the Food Safety and Inspection Service’s 

(FSIS) August 2011, Pesticide Testing Guidance 41

Table 5: Pesticides Tested for in Beef, Pork, and Poultry Included, 

or Planned for Inclusion, in the Food Safety and 

Inspection Service’s (FSIS) National Residue Program, as 

of July 2014 46

Table 6: Percentage of Samples with One or More Detected 

Pesticide Residues in the Most Recent Year of Testing by 

the Agricultural Marketing Service’s (AMS) Pesticide Data 

Program 50

Table 7: Average Number of Pesticides Detected per Sample in 

the Most Recent Year of Testing by the Agricultural 

Marketing Service’s (AMS) Pesticide Data Program 51

Table 8: Highest Average Pesticide Residue Concentration as a 

Percentage of Tolerance in the Most Recent Year of 

Testing by the Agricultural Marketing Service’s (AMS) 

Pesticide Data Program 52

Table 9: Results of FDA Pesticide Residue Tolerance Compliance 

Testing of Apples from 1993 through 2012, by Violation 

Type and Origin 76

Table 10: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Bananas from 1993 through 2012, 

by Violation Type and Origin 77

Table 11: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Broccoli from 1993 through 2012, 

by Violation Type and Origin 78
Page iii GAO-15-38 Pesticide Residue Monitoring

Table 12: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Cantaloupe from 1993 through 

2012, by Violation Type and Origin 79

Table 13: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Green Beans from 1993 through 

2012, by Violation Type and Origin 80

Table 14: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Lettuce from 1993 through 2012, 

by Violation Type and Origin 81

Table 15: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Peaches from 1993 through 2012, 

by Violation Type and Origin 82

Table 16: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Pears from 1993 through 2012, by 

Violation Type and Origin 83

Table 17: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Potatoes from 1993 through 2012, 

by Violation Type and Origin 84

Table 18: Results of FDA Pesticide Residue Tolerance 

Compliance Testing of Sweet Bell Pepper from 1993 

through 2012, by Violation Type and Origin 85

Table 19: Agricultural Marketing Service (AMS) Pesticide Data 

Program Data Selected for Analysis for the Most Recent 3 

Years of Testing of the Commodity 87

Table 20: Average Number of Pesticides Detected per Commodity 

Sample, Using Restricted Agricultural Marketing Service 

(AMS) Data for the Most Recent 3 Years of Testing 89

Table 21: Pesticide Residue with the Highest Average 

Concentration Relative to That Pesticide’s Tolerance, 

Using Restricted Agricultural Marketing Service (AMS) 

Data 91

Table 22: Comparison of the Average Number of Pesticides 

Detected per Sample, Using Restricted and Unrestricted 

Agricultural Marketing Service (AMS) Data from the Most 

Recent Year of Testing 93

Table 23: Comparison of Restricted and Unrestricted Agricultural 

Marketing Service (AMS) Data for Pesticide Residue with 

the Highest Average Concentration Relative to That 

Pesticide’s Tolerance for the Most Recent Year of Testing 95
Page iv GAO-15-38 Pesticide Residue Monitoring

Figures

Figure 1: Estimated Number of Pounds of Conventional Pesticide 

Active Ingredients Used in U.S. Agricultural Sector, 1970 

through 2007 6

Figure 2: Frequency and Rate That Domestic and Imported 

Targeted Samples of 10 Selected Commodities Had One 

or More Pesticide Residue Violations Detected by FDA, 

2008 through 2012 17

Figure 3: Total Number of Pesticide Residue Violations Detected 

by FDA in Targeted Samples of 10 Selected 

Commodities, by Violation Type, 2008 through 2012 19

Figure 4: Total Number of Targeted Samples of Domestic and 

Imported Foods Tested for Pesticide Residues by FDA, 

Fiscal Years 1993 through 2012 24

Abbreviations

AMS Agricultural Marketing Service

EPA Environmental Protection Agency

FDA Food and Drug Administration

FFDCA Federal Food, Drug, and Cosmetic Act

FIFRA Federal Insecticide, Fungicide, and Rodenticide Act

FSIS Food Safety and Inspection Service

HHS Department of Health and Human Services

MOU Memorandum of Understanding

OMB Office of Management and Budget 

PREDICT Predictive Risk-based Evaluation for Dynamic 

 Import Compliance Targeting

USDA U.S. Department of Agriculture

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Page 1 GAO-15-38 Pesticide Residue Monitoring

441 G St. N.W.

Washington, DC 20548

October 7, 2014

The Honorable Paul D. Tonko

Ranking Member

Subcommittee on Environment and the Economy

Committee on Energy and Commerce

House of Representatives

Dear Mr. Tonko:

The domestic and international farmers, ranchers, and other agricultural 

producers who contribute to the U.S. food supply often use insecticides, 

herbicides, or other pesticides to protect their products from insects, 

weeds, fungi, and other pests. In some instances, food producers may 

use multiple pesticides in sequence or simultaneously. The U.S. 

Environmental Protection Agency (EPA) estimated that domestic farmers 

used over 680 million pounds of pesticides for agricultural purposes in 

2007, the latest year for which EPA has national data.1

Three federal agencies—EPA, the U.S. Department of Agriculture 

(USDA), and the Food and Drug Administration (FDA)—regulate various 

aspects of pesticide chemical residues (pesticide residues). EPA 

regulates the amount of pesticide residues that can remain on or in food 

or animal feed. Specifically, EPA sets tolerances—the maximum amount 

of a pesticide residue that is allowed to remain on or in a food. By law, 

residue of pesticides for which EPA has not set a tolerance, or an 

exemption from a tolerance, is considered unsafe and therefore 

prohibited in foods. Although EPA does not have the authority to enforce 

the tolerances it sets, it coordinates with USDA and FDA, which have 

enforcement authority, on which pesticides to include in their monitoring 

While pesticides 

can protect agricultural products from pests, pesticide residues that 

remain on food may also harm consumers. For example, residues may 

affect human nervous and endocrine systems or be carcinogenic. To 

reduce the risk of harm from exposure to pesticides, federal regulations 

establish acceptable levels of residue on and in foods, including animal 

feed.

 

1

EPA collected data on pesticide usage from a combination of public and private sources. 

EPA officials said the agency has not published more recent data in part because it has 

not had funds to purchase data from private sources. 
 

Page 2 GAO-15-38 Pesticide Residue Monitoring

and enforcement programs. Under its National Residue Program, USDA’s 

Food Safety and Inspection Service (FSIS) monitors meat, poultry, and 

processed egg products for pesticide residue and takes enforcement 

actions if it finds pesticide residues that exceed EPA tolerance levels.2

FDA monitors pesticide residues, among other things, in foods it inspects, 

including fruits, vegetables, dairy products, seafood, and spices. FSIS’s 

and FDA’s jurisdiction and monitoring and enforcement activities extend 

to both domestic and imported foods. In addition, USDA’s Agricultural 

Marketing Service (AMS) implements the Pesticide Data Program in 

conjunction with state agencies to survey, on an annual basis, pesticide 

residues in fruits, vegetables, and other foods. The program provides 

EPA with the residue data it needs to assess potential dietary exposure to 

various pesticides. EPA uses these and other data to estimate exposure, 

assess risk, and make registration decisions for pesticide uses.3

In this context, you asked us to review the federal government’s oversight 

of pesticide residue tolerances for food. This report examines (1) what 

FDA data show with respect to pesticide residue violations in the foods 

that it regulates and limitations, if any, in its efforts to monitor foods for 

pesticide violations; (2) what FSIS data show with respect to pesticide 

residue violations in the foods that it regulates and limitations, if any, in its 

efforts to monitor foods for pesticide violations; and (3) what AMS data 

show with respect to pesticide residue levels in fruits, vegetables, and 

other foods, and limitations, if any, in its efforts to gather and report that 

information.

To address these objectives, we analyzed residue data collected by FDA, 

FSIS, and AMS and reviewed the methods the agencies have used to 

 

2 In this context, meat products covered by FSIS inspection include those from cattle, 

sheep, swine, goats, horses, mules, and other equines. Poultry includes any domesticated 

bird. Processed egg products include any dried, frozen or liquid eggs, with or without 

added ingredients. Processed egg products do not include whole, unbroken eggs.

3

Under the Federal Insecticide, Fungicide, and Rodenticide Act, EPA registers pesticides 

for distribution, sale, and use in the United States and prescribes labeling and other 

regulatory requirements to prevent unreasonable adverse effects on the environment. To 

obtain a registration, a company or person (registrant) must provide data in support of 

registration including tests made and results, flagging any potential adverse effects. If the 

registration is for a food use pesticide, the applicant must also submit a petition for all 

needed tolerances. EPA may register the pesticide and set a tolerance level for those 

pesticides used on food or animal feed, notify the registrant of deficiencies in the data or 

need for additional information, or reject the application.
 

Page 3 GAO-15-38 Pesticide Residue Monitoring

collect those data. We analyzed FDA and AMS data on samples of 

domestic and imported fruits and vegetables—the categories of 

commodities most often tested by these two agencies—and FSIS data on 

meat, poultry, and processed egg products. To report what FDA data 

show with respect to residue violations, we examined data on violations it 

detected in 10 highly consumed fruit and vegetable commodities 

(selected commodities) for fiscal years 1993 through 2012, excluding 

2004:4 apples, bananas, broccoli, cantaloupe, green beans, lettuce, 

peaches, pears, potatoes, and sweet bell peppers. We chose to focus our 

analysis of pesticide residue violations detected by FDA over a 5-year 

period (for fiscal years 2008 through 2012) because rates based on a 

small number of samples are unstable.5 We also present data on 

pesticide residue violations detected in the 10 commodities from 1993 

through 2012 in appendix II. Those data include years in which FDA 

generally took larger sample sizes than it did from 2008 through 2012. In 

addition, we examined recent FDA data on violations in other imported 

foods.6 To report what FSIS data show with respect to pesticide residue 

violations, we analyzed the agency’s National Residue Program data for 

meat, poultry, and processed egg products from calendar years 2000 

through 2011, the years for which FSIS’s annual reports were available. 

To report what AMS data show with respect to pesticide residues in fruits 

and vegetables, we analyzed the agency’s Pesticide Data Program test 

results for the same 10 commodities for which we analyzed FDA data. 

We selected these 10 commodities because they were the commodities 

AMS tested for most often since 1994.7

 

4

FDA was not able to provide us with test results from 2004 that were comparable in detail 

to the other years. Therefore, we could not include that year in our analysis of pesticide 

residue test results.

Specifically, we analyzed AMS 

data from the 3 most recent years in which the agency tested each of the 

5 By grouping data from the 5 most recent years available, we balance the desire to 

present recent data with the need to have enough samples to present violation rates. We 

also report the samples and violation counts for each of the 5 years separately in order to 

display the range of sample sizes and violation counts over these years. 

6

We examined data on imported commodities—including fruits and vegetables—FDA 

found to have high rates of pesticide tolerance violations in fiscal years 2007 through 

2011. 

7

AMS began the Pesticide Data Program in 1991. However, AMS officials advised us to 

begin our analysis with data from 1994 because the data prior to that year are not in a 

comparable format. 
 

Page 4 GAO-15-38 Pesticide Residue Monitoring

10 commodities for calendar years 1998 through 2012.8 In using the 

agencies’ data, we evaluated the reliability of these data by reviewing or 

discussing the agencies’ management controls to ensure its accuracy and 

completeness. As appropriate, we also reviewed the agencies’ 

compliance with the Office of Management and Budget’s (OMB) 

Standards and Guidelines for Statistical Surveys.

9 We found these data to 

be sufficiently reliable for purposes of reporting what the agencies have 

found regarding pesticide residues and residue violations in food, 

although, where discussed, we note limitations in the methods the 

agencies have used to collect these data. To examine the recent methods 

FDA and FSIS have used to detect pesticide residue violations, we 

reviewed appropriate agency policy directives, reports, and other 

documents to better understand the agencies’ residue monitoring 

programs. In addition, we analyzed FDA’s use of its risk-based tool for 

selecting imported foods for pesticide residue testing, known as 

Predictive Risk-based Evaluation for Dynamic Import Compliance 

Targeting (PREDICT).10

 

8 The years in which AMS tested samples are not the same for every commodity because 

AMS uses a staggered sampling schedule. According to AMS officials, highly consumed 

commodities are rotated into the program every 5 years and tested for a period of 2 

consecutive years.

We interviewed officials in FDA’s Center for Food 

Safety and Applied Nutrition who are responsible for developing 

strategies and policies for reducing health threats from contaminated food 

and officials from FDA’s Office of Regulatory Affairs who are responsible 

for monitoring foods for pesticide residue and enforcing pesticide 

tolerances. We interviewed officials in FSIS’s Office of Public Health 

Science who are responsible for managing the agency’s National Residue 

Program for meat, poultry, and processed egg products. We also 

interviewed agency officials in AMS’s Monitoring Programs Division who 

are responsible for managing the Pesticide Data Program. Within EPA, 

we interviewed officials in the Office of Pesticide Programs who are 

responsible for using data generated by FDA, USDA, and others to 

9

OMB, Standards and Guidelines for Statistical Surveys (September 2006). 

10FDA uses PREDICT to identify imported food samples for testing for pathogens and 

other contaminants, including pesticides. FDA also uses the tool to identify other products 

for review prior to admission into the country, such as medical devices and 

pharmaceutical drugs. The PREDICT tool is web-based and designed to help border 

inspectors monitor products, especially high-risk ones, at ports of entry. PREDICT uses 

historical data, patterns, and violations to generate a numerical score for FDA-regulated 

imported products.
 

Page 5 GAO-15-38 Pesticide Residue Monitoring

assess health risks associated with exposure to pesticides. Appendix I 

provides a more detailed description of our objectives, scope, and 

methodology.

We conducted this performance audit from November 2012 to October 

2014 in accordance with generally accepted government auditing 

standards. Those standards require that we plan and perform the audit to 

obtain sufficient, appropriate evidence to provide a reasonable basis for 

our findings and conclusions based on our audit objectives. We believe 

that the evidence obtained provides a reasonable basis for our findings 

and conclusions based on our audit objectives.

This section provides information on trends in agricultural pesticide use in 

the United States; growth in the volume of foods imported into the 

country; and the potential human health effects of exposure to pesticide 

residues and key responsibilities that EPA, FDA, and USDA’s FSIS and 

AMS have with respect to pesticide residues in food.

Conventional pesticide use in the U.S. agricultural sector grew from 1970 

through 1979 and then generally trended downward through 2007 (see 

fig. 1).11 According to a 2011 EPA report, the U.S. agricultural sector used 

an estimated 684 million pounds of conventional pesticides in 2007, the 

latest year for which the agency has published data.12

 

11In this context, the term conventional pesticides includes herbicides (i.e., weed killers), 

plant growth regulators (i.e., chemicals used to alter the expected growth, flowering, or 

reproduction rate of plants), insecticides (i.e., chemicals used to kill insects and other 

arthropods), miticides (i.e., chemicals used to kill mites that feed on plants and animals), 

fungicides (i.e., chemicals used to kill fungi, including blights, mildews, molds, and rusts), 

nematicides (i.e., chemicals used to kill nematodes—microscopic, worm-like organisms 

that feed on plant roots), and fumigants (i.e., chemicals that produce gas or vapor 

intended to destroy pests in buildings or soil).

This was an 

12EPA, Pesticides Industry Sales and Usage: 2006 and 2007 Market Estimates, Biological 

and Economic Analysis Division, Office of Pesticide Programs, Office of Chemical Safety 

and Pollution Prevention, Washington, D.C. 20460 (February 2011). According to EPA, 

neither it nor any other federal agency has a program devoted specifically to estimating 

the overall quantity of active ingredient used on an annual basis. EPA noted its report 

uses the best available information from the public domain and private marketing research 

companies (proprietary data sources). The numbers in EPA’s report represent 

approximate values rather than precise values with known statistical properties. 

Background

Trends in Agricultural 

Pesticide Use in the 

United States
 

Page 6 GAO-15-38 Pesticide Residue Monitoring

increase from 643 million pounds in 2006, but well below the peak of 843 

million pounds in 1979.

Figure 1: Estimated Number of Pounds of Conventional Pesticide Active Ingredients Used in U.S. Agricultural Sector, 1970 

through 2007

Note: The latest year for which EPA has published data on estimated pesticide usage is 2007. The 

figure depicts use of conventional pesticides only, excluding sulfur, petroleum oil, and other chemicals 

used as pesticides (e.g., sulfuric acid and insect repellents), wood preservatives, specialty biocides, 

and chlorine/hypochlorites. Active ingredient refers to the chemical or substance component of a 

pesticide product intended to kill, repel, attract, mitigate, or control a pest, or that acts as a plant 

growth regulator, desiccant, or nitrogen stabilizer. The term conventional pesticides includes 

herbicides (i.e., weed killers), plant growth regulators (i.e., chemicals used to alter the expected 

growth, flowering, or reproduction rate of plants), insecticides (i.e., chemicals used to kill insects and 

other arthropods), miticides (i.e., chemicals used to kill mites that feed on plants and animals), 

fungicides (i.e., chemicals used to kill fungi, including blights, mildews, molds, and rusts), nematicides 

(i.e., chemicals used to kill nematodes—microscopic, worm-like organisms that feed on plant roots), 

and fumigants (i.e., chemicals that produce gas or vapor intended to destroy pests in buildings or 

soil.)

As a group, the most commonly used pesticides have a variety of 

functions. In 2007, 13 of the top 25 pesticide active ingredients used in 

the agricultural sector were herbicides; 3 were fungicides; 3 were 

insecticides; 5 were fumigants; and 1 was a plant growth regulator. 
 

Page 7 GAO-15-38 Pesticide Residue Monitoring

According to EPA, the most used active ingredient in the U.S. agricultural 

sector from 2001 through 2007 was the herbicide glyphosate.13

EPA’s 2011 report shows that, while the use of some pesticides has 

grown, others have declined. For example, the amount of 

organophosphate insecticides used in all sectors—including agriculture—

declined more than 60 percent from 1990 through 2007, from an 

estimated 85 million pounds in 1990 to 33 million pounds in 2007.

In 2007, 

glyphosate use reached 180 million to 185 million pounds. Other 

pesticides commonly used from 2001 through 2007 were the herbicide 

atrazine, the fumigant metam sodium, and the herbicide metolachlor-S.

14

Organophosphate use as a percentage of total insecticide use decreased 

from 70 percent in 1990 to 35 percent in 2007. These declines were the 

result, in part, of growing concerns over the toxicity of organophosphates. 

Some of the decline occurred after EPA increased its oversight of this 

class of pesticides in response to the Food Quality Protection Act of 1996 

that included provisions to better ensure the health of infants and children 

from pesticide risks.15

The overall use of pesticides in agricultural settings is not necessarily 

indicative of the risk associated with those pesticides. A pound of one 

pesticide, for example, is not necessarily as toxic or potentially harmful to 

human health as a pound of another pesticide. Therefore, a total increase 

or decrease in the amount of pesticides used does not necessarily mean 

that total toxicity or risk has changed at the same rate. We were unable to 

find publicly available estimates of the overall toxicity or risk associated 

with the use of agricultural pesticides in the United States.

 

13Glyphosate is the active ingredient in certain “broad-spectrum” herbicides that are 

effective at killing a range of weeds but that may also kill the crop. The growth in 

glyphosate use is associated with the widespread planting of genetically engineered 

crops—such as corn and soybeans—that can tolerate being sprayed with glyphosate. 

14According to EPA’s website, organophosphates affect the nervous system by disrupting 

the enzyme that regulates acetylcholine, a neurotransmitter. Most organophosphates are 

insecticides. They were developed during the early nineteenth century, but their effects on 

insects, which are similar to their effects on humans, were discovered in 1932. However, 

organophosphates usually are not persistent in the environment. 

15Pub. L. No. 104-170, 110 Stat. 1489.
 

Page 8 GAO-15-38 Pesticide Residue Monitoring

The number of imported food shipments that FDA has responsibility for 

monitoring and testing has increased in recent years. We reported in 

September 2009 that the number of food “entry lines” that passed through 

U.S. ports and for which FDA had oversight authority nearly doubled in 

the previous 10 years to an estimated 9.5 million.16 Since the issuance of 

our report, that number grew to about 9.7 million in 2012. The growth in 

the percentage of imported foods in the U.S. food supply has varied 

widely for different types of foods.17

While the overall growth in imported foods has enhanced consumer 

choice, it has also strained the resources of federal agencies responsible 

for monitoring food safety. Imported foods could pose pesticide risks that 

are different than those posed by domestically grown food if the exporting 

countries have different agricultural practices. For example, growers in 

other countries might use pesticides that are not registered for use in the 

United States and do not have an “import tolerance” that would allow 

residue of that pesticide on imported food.18

 

16GAO, Food Safety: Agencies Need to Address Gaps in Enforcement and Collaboration 

to Enhance Safety of Imported Food, 

FDA and USDA are

responsible for ensuring the safety of imported food to the same extent as 

domestic food. If a food is found to have a pesticide in excess of an 

GAO-09-873 (Washington, D.C.: Sept. 15, 2009). An 

entry line is a unique shipment of imported products or items offered for admission into 

U.S. commerce. On the other hand, we use the term “lot” to indicate a unique quantity of a 

domestically grown product subject to FDA testing.

17According to USDA’s Economic Research Service, the imported share of U.S. fruit and 

nut consumption grew from 28.1 percent in 1994 to 38.5 percent in 2009, while the 

imported share of U.S. vegetable consumption grew from 7.5 percent to 17.5 percent. 

From 1994 through 2009, seafood imports increased from about 56 percent to about 85 

percent of the total amount consumed in the United States. In contrast, imported red meat, 

poultry, dairy, and egg products have generally remained constant as a percentage of the 

amount of U.S. consumption from 1994 through 2009.

18When no U.S. registration exists, interested persons may submit a petition requesting 

that EPA establish an import tolerance for a pesticide residue on a food or feed 

commodity, which will allow the food or feed treated with the pesticide in foreign countries 

to be imported into the United States. Therefore, the term “import tolerance” is used to 

refer to a residue tolerance that has been established for a pesticide for which there is no 

accompanying U.S. registration, but which meets U.S. food safety standards. Interested 

persons may also submit a petition requesting that EPA exempt a pesticide from the need 

for an import tolerance, which EPA may grant if it determines, among other things, that 

there is a reasonable certainty that no harm will result from aggregate exposure to the 

residue, including all anticipated dietary exposures and all other nonoccupational 

exposures for which there is reliable information.

Growth in the Volume of 

Imported Foods Regulated 

by FDA
 

Page 9 GAO-15-38 Pesticide Residue Monitoring

import tolerance, or if no tolerance has been set, the food is considered 

unsafe and cannot enter commerce in the United States.

According to EPA’s website, the health effects of pesticides depend on 

the type of pesticide. Some, such as the organophosphates and 

carbamates, affect the nervous system. Others may irritate the skin or 

eyes; some may be carcinogens; and others may affect the hormone or 

endocrine systems in the body. Also, according to EPA’s website, the 

specific health effects of a particular pesticide depends on the pesticide’s 

toxicity and how much of it is consumed (i.e., exposure). EPA also notes 

that infants and children may be especially sensitive to health risks posed 

by pesticides.

EPA, FDA, and USDA’s FSIS and AMS each have key responsibilities 

with respect to pesticide residues in food.

The primary federal laws that govern how EPA regulates pesticides in the 

United States are the Federal Insecticide, Fungicide, and Rodenticide Act 

(FIFRA) and the Federal Food, Drug, and Cosmetic Act (FFDCA).19

Under FIFRA and its implementing regulations,20

 

197 U.S.C. §§ 136-136y, 21 U.S.C. §§ 301-399d; see specifically 7 U.S.C. § 136a, 21 

U.S.C. § 346a. The Antimicrobial Regulation Technical Corrections Act of 1998 amended 

the definition of “pesticide chemical” in the FFDCA by, in part, excluding certain 

antimicrobial substances from the definition of pesticide chemical. Pub. L. No. 105-324, 

112 Stat. 3035. Substances so excluded became subject to regulation by FDA as food 

additives. This report does not address antimicrobial substances that may be regulated by 

EPA as pesticide chemical residues or by FDA as food additives.

EPA is to review 

applications for pesticide products and register those that it determines 

will meet FIFRA’s statutory standards. Generally, unless it is registered 

with EPA for use on a particular commodity, a pesticide cannot be legally 

used on that commodity. Of particular relevance to EPA’s review, if the 

use of a pesticide would result in a residue of the substance in or on food 

or animal feed, generally, EPA may not register that pesticide unless it 

can determine that the residue is “safe” as defined by FFDCA. Under 

FFDCA, with regard to a pesticide residue, safe means that EPA has 

determined, among other things, that there is a reasonable certainty that 

no harm will result from aggregate exposure to the residue, including all 

anticipated dietary exposures and all other nonoccupational exposures for 

207 U.S.C. § 136a; 40 C.F.R. pts. 152-180.

Potential Health Effects of 

Exposure to Pesticide 

Residues and Agency 

Responsibilities

EPA Sets Pesticide Tolerances
 

Page 10 GAO-15-38 Pesticide Residue Monitoring

which there is reliable information. Nonoccupational exposures are those 

experienced by the general population, as opposed to those experienced 

by specific groups of pesticide users (i.e., occupational users), such as 

farm workers and pest control operators. EPA may establish a tolerance 

level—the maximum permissible pesticide residue in or on food or animal 

feed that is sold—that meets the FFDCA safety standard for a pesticide 

residue or may choose to grant a tolerance exemption if it determines that 

the exemption meets the FFDCA safety standard for a pesticide 

residue.21

EPA typically sets tolerances in response to a petition from the pesticide 

manufacturer to register the pesticide for use in association with a 

particular commodity.22 For example, EPA has established a tolerance of 

0.05 parts per million for the insecticide chlorpyrifos on cucumber and a 

tolerance of 1 part per million for the herbicide diuron on pears.23

 

21Registration of a pesticide is not, however, a prerequisite for establishing a tolerance. 

For example, EPA may establish a temporary tolerance to permit the experimental use of 

a nonregistered pesticide, or EPA may establish a tolerance for a pesticide residue 

resulting from the use of the pesticide in food or animal feed in a foreign country.

Tolerances for pesticides may differ depending on the commodity. For 

example, although the tolerance for chlorpyrifos is 1 part per million on 

cherries, it is 2 parts per million on radishes. According to EPA officials, 

the different tolerances reflect the agency’s analysis of different chemicalspecific and crop-specific agricultural practices and the expected residues 

that would result from those practices. From a regulatory perspective, it is 

also important to be aware of those situations in which EPA has not 

established a tolerance for a pesticide on a particular commodity. For 

example, although EPA has set a tolerance for diuron on pears, it has not 

set a tolerance for that herbicide on mushrooms, lettuce, or many other 

22Pesticide manufacturers go to some effort and expense to get a pesticide registered for 

a particular use. In light of this expense, they may choose not to seek registration for a 

pesticide to be used on all potential commodities if they do not expect the use on those 

commodities to be commercially significant. In 1963, the directors of state agricultural 

experiment stations began a program known as IR-4. The IR-4 program continues to this 

day, and with funding from USDA, land grant universities, and the agrochemical industry, 

works with EPA to register pesticides for use on commodities for which the manufacturer 

has not applied.

23Tolerances for residues in raw commodities apply to those same residues in processed 

commodities. If the residues in processed commodities are expected to exceed the 

residues in the raw commodity, a separate processed food tolerance is needed. 
 

Page 11 GAO-15-38 Pesticide Residue Monitoring

commodities. Therefore, residues of diuron are not permitted on those 

commodities.

Under FFDCA, FDA is responsible for protecting the public health by 

ensuring that the food subject to its jurisdiction—including fruits, 

vegetables, dairy products, seafood, and spices—is safe, wholesome, 

sanitary, and properly labeled. In meeting its responsibility, FDA monitors 

pesticide residues, among other things, in foods it inspects. The agency’s 

efforts include testing domestic and imported foods in interstate 

commerce for the presence of pesticide residues.24 According to FDA’s 

website, this responsibility entails annual oversight of more than $400 

billion in domestic foods and about $50 billion in imported foods. FDA’s 

Compliance Program Guidance Manual states that the agency’s 

objectives are to (1) enforce pesticide residue tolerances in foods 

established by EPA and (2) determine the incidence and level of pesticide 

residues in domestic and imported foods.25

FDA typically collects samples of domestic foods for testing close to the 

point of production in the distribution system, (i.e., from growers, packers, 

and distributors), while it collects imported foods for testing at the point of 

entry into U.S. commerce.

FDA’s guidance manual 

identifies pesticides and classes of pesticides but does not identify each 

pesticide for which the agency must test. FDA uses two broad categories 

of testing technology. One type of test—known as a multiresidue 

method—can detect many pesticides, and the other type—a selective 

residue method—can detect one specific pesticide. No one test can 

detect all possible pesticide residues.

26

 

24In addition, FDA monitors domestic and imported foods in interstate commerce for 

pathogens, natural toxins, heavy metals, and other contaminants. 

When testing raw commodities such as fruits 

and vegetables for pesticide residues, FDA conducts its tests on 

unwashed, whole (unpeeled) items. FDA also tests processed foods such 

as breakfast cereals and snack foods for pesticide residues.

25FDA, Compliance Program Guidance Manual: Chapter 04—Pesticide and Chemical 

Contaminants, 7304.004 (June 27, 2011).

26The amount (e.g., containers or pounds) of a commodity that FDA samples may vary by 

commodity. Two examples of amounts are one intact shipping case or a total of 20 

pounds for fresh produce. 

FDA Monitors Most Foods for 

Pesticide Residue Violations
 

Page 12 GAO-15-38 Pesticide Residue Monitoring

If FDA finds pesticide residues that exceed established tolerances for a 

specific commodity—or pesticide residues for which there are no 

established tolerances for that commodity—it may take a variety of 

enforcement actions. For example, FDA can refuse entry of food offered 

for import into the United States or seize foods in domestic commerce 

that exceed an EPA tolerance or are found to contain pesticide residues 

for which there is no tolerance. FDA may allow a food to be 

“reconditioned” or diverted to another use.27

In December 2011, FDA completed the national rollout of PREDICT, a 

tool the agency expects will (1) improve import screening and targeting to 

prevent entry of goods that are adulterated,

If FDA finds that an imported 

food has a pesticide residue violation, it may issue an “import alert” 

covering subsequent shipments of that product from the shipper or 

grower. FDA officials at ports of entry would then detain without physical 

examination any future shipments of that product from that shipper or 

grower unless the importer provides proof that the product did not contain 

residues of the pesticide(s) cited in the import alert in excess of the 

established tolerance. FDA may also issue an import alert for a food 

product from an entire country or geographic area. To be exempt from the 

alert, shippers or growers of a specific product from a specific location are 

asked to provide evidence that their products comply with EPA 

tolerances. FDA may also request that a company conduct a recall if it 

determines that domestic or imported foods that have entered the food 

supply have pesticide residues that violate established tolerances or are 

found to contain pesticide residues for which EPA has not established a 

tolerance. Generally, FDA has the authority to order a food recall if it 

would cause serious adverse health consequences or death to humans or 

animals and the company fails to voluntarily recall the product.

28 misbranded or otherwise 

violate FDA standards (i.e., violative); and (2) expedite the entry of goods 

that do not violate FDA standards (i.e., nonviolative).29

 

27One option would be to divert the product from food for human consumption to food for 

animal consumption if it would meet the established tolerance for animal food.

With PREDICT, 

28Food is deemed to be adulterated under the Federal Food, Drug, and Cosmetic Act if, 

among other things, it bears or contains a pesticide chemical residue in excess of an 

established tolerance, or, when no tolerance exists, any residue is present and there is no 

exemption from the tolerance requirement granted. 

29The tool is not specific to pesticide residues in food; FDA uses it for all types of products 

within its jurisdiction.
 

Page 13 GAO-15-38 Pesticide Residue Monitoring

FDA gathers specific information about products, manufacturers, or 

growers, country of origin, and other factors to generate a risk score for 

each line in an entry. The higher the cumulative score, the greater the 

identified risk. FDA officials at ports of entry may use the risk scores and 

import alerts to make decisions about which products can be released 

into the country and which should receive further examination such as 

laboratory testing for pesticide residues. FDA does not use a similar tool 

for screening domestic foods for sampling. FDA’s guidance directs its 

district offices to develop sampling plans that consider similar information, 

such as past violations, pesticide usage, and other information gathered 

by the district.

FDA also acquires data on particular commodity and pesticide 

combinations by conducting market basket surveys under its Total Diet 

Study. This annual survey is distinct from regulatory monitoring in that it 

determines pesticide residues in foods that are prepared and table-ready 

for consumption. The foods are washed, peeled, or cooked before 

analysis, simulating typical consumer handling. Each survey comprises 

about 300 different foods that represent the average U.S. consumer’s 

diet, which FDA tests with methods that are 10 to 100 times more 

sensitive than FDA’s regulatory monitoring procedures, meaning that they 

can detect much lower concentrations of residue. We did not examine the 

results of this study because its sample sizes for each commodity tested 

are small.30

Under the Federal Meat Inspection Act, the Poultry Products Inspection 

Act, and the Egg Products Inspection Act, USDA’s FSIS is responsible for 

examining and inspecting to prevent the distribution of adulterated food 

products. To meet this responsibility, FSIS, among other things, monitors 

meat, poultry, and processed egg products for pesticide residue.31

 

30FDA typically tests four “market baskets” of each type of food per year. Each market 

basket is a composite of the food collected from three cities in one of four regions of the 

country. FDA surveys different cities from year to year.

FSIS 

executes this responsibility as part of its National Residue Program under 

which it randomly samples domestic and imported meat, poultry, and 

processed egg products to test for pesticides; veterinary drugs; and 

31A meat, poultry, or egg product is considered adulterated under federal law if, among 

other circumstances, it bears or contains a pesticide chemical residue in excess of an 

established tolerance, or, when no tolerance exists, any residue is present and there is no 

exemption from the tolerance requirement granted.

FSIS Monitors Meat, Poultry, 

and Processed Egg Products 

for Pesticide Residue 

Violations
 

Page 14 GAO-15-38 Pesticide Residue Monitoring

environmental contaminants, such as heavy metals, that might find their 

way into these products destined for human consumption. FSIS takes 

samples of domestic products at slaughterhouses and processing 

facilities and samples imported products at ports of entry. In each case, 

FSIS tests products for pesticide residues at its Western Laboratory in 

California using the multiresidue method. On December 10, 2012, FSIS 

published a new policy stating that slaughterhouse and import 

establishments must maintain control of livestock products while awaiting 

the results of tests for contaminants.32

USDA’s AMS coordinates with state agencies to conduct an annual 

survey of pesticide residues in and on fruits, vegetables, and other food 

commodities known as the Pesticide Data Program. AMS does not 

conduct this survey to enforce EPA pesticide tolerances; rather, its 

primary purpose is to collect residue data that EPA uses to assess the 

dietary exposure associated with particular pesticides. However, FDA can 

review Pesticide Data Program data for possible violations and can use 

those data to inform its own enforcement program. In 2012, AMS decided 

that it would no longer collect residue data for beef, pork, and poultry 

products, with the expectation that FSIS would provide such data to EPA.

According to AMS documents, it uses random sample selection methods 

to obtain a statistically valid representation of the U.S. food supply. In 

recent years, the survey has annually tested domestic and imported 

samples of 20 to 30 commodities. The list of commodities tested changes 

from year to year and, over the history of the program, AMS has tested 

about 90 different types of food. In recent years, AMS has established 

cooperative agreements with about a dozen states to participate in the 

program. State officials, under the direction of AMS, collect foods at 

terminal markets33

 

32The new policy does not apply to poultry. The FSIS policy stated that poultry did not 

need to be held from commerce pending negative test results because of (1) the 

significant number of poultry carcasses in a lot; (2) the economic effects of holding a lot; 

and (3) historically, FSIS has not seen contaminant problems (of any type) in poultry 

tested for residues.

and distribution centers for large chain stores. 

Participation by the terminal markets and distribution centers in the 

program is voluntary. Depending on the commodity, the foods are tested 

for residue at either state or federal laboratories. Because AMS conducts 

33A terminal market is an organized wholesale market into which large quantities of 

agricultural produce, livestock, or other goods are shipped for distribution and sale.

AMS Collects Data for Annual 

Survey of Pesticide Residues
 

Page 15 GAO-15-38 Pesticide Residue Monitoring

residue testing to gather information for EPA to use in conducting risk 

assessments rather than for regulatory purposes, some of the foods are 

handled as AMS expects consumers to handle them. For example, fruits 

and vegetables may be washed, cored, or peeled before being tested.

FDA data for the 10 commodities we reviewed show the agency found 

low rates of pesticide residue violations as part of targeted (i.e., 

nongeneralizeable) monitoring for compliance and enforcement, but 

FDA’s approach for detecting violations has limitations. Specifically, we 

found that FDA takes relatively few targeted samples to test for pesticide 

residue and detects what is likely to be a small percentage of the foods 

that have violative levels of residue.34 Moreover, FDA does not disclose in 

its annual monitoring reports that it does not test for some commonly 

used pesticides that have established tolerances for many commodities. 

In addition, it is not clear to what extent FDA’s recently implemented 

targeting tool for imported foods—PREDICT—helps the agency identify 

foods most likely to have pesticide residue violations. Furthermore, 

because FDA does not use statistically valid methods to gather residue 

data, it is not able to meet its objective to determine the incidence and 

level of pesticide residues in domestic and imported foods.

From 2008 through 2012, FDA’s compliance and enforcement monitoring 

program, which carries out one of the agency’s objectives of enforcing 

pesticide residue tolerances in foods established by EPA, detected low 

rates of pesticide residue violations35

 

34FDA uses the term “sample” when reporting pesticide residue test results for domestic 

and imported foods. However, FDA clearly notes in its annual reports that it does not 

randomly select its samples. Therefore, the results of its samples are not meant to be 

used to generalize to a larger population of foods. Consequently, we use the term targeted 

sample to distinguish from more random sampling methods used by FSIS and AMS. 

among the targeted samples it 

tested of the 10 commonly consumed fruit and vegetable commodities we 

reviewed. We found that the violation rates among foods it tested varied 

by commodity. For example, over that 5-year period of time, FDA 

detected one or more residue violations in 0 to 1.9 percent of its samples 

of apples, bananas, broccoli, lettuce, and potatoes and detected one or 

35A violation is either due to the presence in or on a commodity of a pesticide that 

exceeds the tolerance established by EPA (a violation of tolerance) or the presence of a 

pesticide for which EPA has not established a tolerance for that commodity (a violation of 

no tolerance). 

FDA Data Show Low 

Rates of Pesticide 

Residue Violations, 

but FDA’s Approach 

for Detecting 

Violations Has 

Limitations That Are 

Not Disclosed

FDA Has Found Few 

Violations, and Violation 

Rates Have Varied Among 

the Foods It Tests as Part 

of Its Compliance and 

Enforcement Monitoring
 

Page 16 GAO-15-38 Pesticide Residue Monitoring

more violations in 3.3 to 5.4 percent of its samples of cantaloupe, green 

beans, peaches, pears, and sweet bell peppers. Figure 2 provides data 

on the extent to which domestic and imported samples of the 10 selected 

commodities FDA tested had one or more violations from 2008 through 

2012. The agency collected these data as part of its risk-based targeting, 

a selection method designed to target foods with a high risk of violation36

rather than to estimate the incidence or prevalence of pesticide residues 

on all commodities; therefore, these data are not meant to be generalized 

to all foods the agency regulates.37 FDA data also show that the agency 

generally found low rates of pesticide residue violations among its 

samples of the 10 selected commodities in the years from 1993 through 

2007 and that the rates varied by commodity and year. See appendix II 

for a presentation of year-by-year results on sample and violation counts 

broken down by commodity, violation type, and origin for 1993 through 

2012, with the exception of 2004.38

 

36Factors that affect risk-based targeting include the history of violations for particular 

commodities or places of origin. 

37We present violation rates for a 5-year period rather than for individual years because 

rates based on a small number of samples are unstable. By grouping data from the 5 most 

recent years available, we balance the desire to present recent data with the need to have 

enough samples to present violation rates. We also report the samples and violation 

counts for each of the 5 years separately in order to display the range of sample sizes and 

violation counts over these years. 

38As noted, FDA was not able to provide us with test results from 2004 that were 

comparable in detail to the other years. Therefore, we could not include that year in our 

analysis of pesticide residue test results. 
 

Page 17 GAO-15-38 Pesticide Residue Monitoring

Figure 2: Frequency and Rate That Domestic and Imported Targeted Samples of 10 Selected Commodities Had One or More 

Pesticide Residue Violations Detected by FDA, 2008 through 2012

Note: FDA may have detected more than one violation on a single sample. The violations 

represented in the figure are one of two types: violations of no tolerance and violations of tolerance. A

violation of no tolerance means that FDA has detected residue of a pesticide on a commodity for 

which EPA has not established a tolerance. A violation of tolerance means that FDA has detected a 

pesticide residue that exceeds the EPA-established tolerance for that commodity. The violation rate 

presented in the table for each commodity represents the overall rate that FDA detected from fiscal 

years 2008 through 2012. FDA uses the term “sample” when reporting pesticide residue test results 

for domestic and imported foods. However, FDA notes in its annual pesticide monitoring reports that it 

does not randomly select its samples. Therefore, the results of its samples are not meant to be used 

to generalize to a larger population of foods. Consequently, we use the term targeted sample to 

distinguish from random sampling methods.

Our analysis also shows that FDA detected more than one violation in 

some samples of the 10 selected commodities. For example, from 2008 

through 2012, of the 10 samples of potatoes with one or more violations 

detected (see fig. 2), FDA detected 24 residue violations as shown in 

figure 3. We also found that violations of no tolerance were the most 

common type of violation FDA detected in 7 of the 10 selected 
 

Page 18 GAO-15-38 Pesticide Residue Monitoring

commodities.39

 

39Our analysis focuses on two types of violation; violations of no tolerance and violations 

of tolerance. FDA also may establish, as guidance, a nonbinding level, known as an action 

level, for an unavoidable residue of a cancelled pesticide that persists in the environment. 

From 2008 through 2012, FDA detected 7 instances among the 10 select commodities 

where an unavoidable residue level exceeded an action level for the commodity.

These violations occur when FDA detects a pesticide for 

which there is no established tolerance for the particular commodity on 

which it was found. For example, 38 of 41 violations detected in sweet 

bell peppers and 8 of 11 violations detected in peaches from 2008 

through 2012 were violations of no tolerance. During the same period, 

FDA detected violations of established tolerances—instances in which the 

concentration of a pesticide residue exceeded the limit established by 

EPA—more frequently in its targeted samples of broccoli and potatoes. 

FDA detected no violations of either type in bananas in those years. See 

figure 3 for FDA’s findings for the number of each of the two types of 

violations detected from 2008 through 2012 in the 10 selected 

commodities.
 

Page 19 GAO-15-38 Pesticide Residue Monitoring

Figure 3: Total Number of Pesticide Residue Violations Detected by FDA in Targeted Samples of 10 Selected Commodities, by 

Violation Type, 2008 through 2012

Note: Figure 3 shows data on two types of violations. A violation of no tolerance means that FDA has 

detected residue of a pesticide on a commodity for which EPA has not established a tolerance. A 

violation of tolerance means that FDA has detected a pesticide residue that exceeds the EPAestablished tolerance for that commodity. FDA uses the term “sample” when reporting pesticide 

residue test results for domestic and imported foods. However, FDA notes in its annual pesticide 

monitoring reports that it does not randomly select its samples. Therefore, the results of its samples 

are not meant to be used to generalize to a larger population of foods. Consequently, we use the term 

targeted sample to distinguish from random sampling methods.

As noted earlier, because FDA data on violations were derived from a 

sampling method designed to target foods with a high risk of violation, 

rather than from a statistically generalizable sample, FDA violation rates 

are not intended to be interpreted as reliable estimates of the actual rates 

of potential violations among these 10 commodities in the food supply. In 

addition, FDA typically collects its samples of domestic foods for testing 

close to the point of production (i.e., from growers, packers, and 

distributors) and collects its samples of imported foods for testing at the 

point of entry into U.S. commerce. In contrast, AMS tests foods that are 

further along the food supply chain—and, thus, closer to consumers—at 

terminal markets and distribution centers. AMS generally tests sample 
 

Page 20 GAO-15-38 Pesticide Residue Monitoring

sizes from 500 to 750 per commodity, which are considerably larger than 

FDA’s sample sizes. The presence of a residue above a tolerance or for 

which there is no tolerance indicates a possible violation that FDA did not 

detect with its targeted sampling. Therefore, to further examine violation 

rates for the 10 selected commodities, we analyzed AMS data on these 

commodities that indicate the presence of pesticide residues in the food 

supply. AMS calls the residues it detects that exceed tolerances or for 

which there are no tolerances “presumptive tolerance violations.” (It is 

also noteworthy that, unlike FDA’s compliance and enforcement 

monitoring program, AMS tests commodities after preparing them as 

consumers are expected to do, such as washing, coring, or peeling fruits 

and vegetables. This practice is likely to reduce pesticide residues and 

lower the rate at which AMS finds presumptive tolerance violations.) We 

found that presumptive tolerance violation rates varied by several orders 

of magnitude across the 10 selected commodities and years tested. 

Specifically, for commodities with presumptive tolerance violations, the 

rates ranged from 0.14 percent on apples in 2001 to 19.47 percent on 

pears in 1998—a 139-fold difference. Table 1 shows the presumptive 

tolerance violation rates for the 3 most recent years in which AMS tested 

the 10 selected commodities for 1998 through 2012.40 For example, as 

shown in table 1, the presumptive tolerance violation rate for peaches in 

2008 was 9.1 percent.41 If that violation rate prevailed (i.e., was a valid 

estimate of violations) for all peaches in that year, it would mean that 

about 9 out of 100 peaches consumed in that year would be expected to 

exceed the maximum permissible pesticide residue level for that fruit.

 

40AMS does not sample each commodity in each year. Therefore, the 3 most recent years 

for one commodity may not match the 3 most recent years for other commodities. The 3 

most recent years of testing from 1998 through 2012 are shown in table 19 in appendix III. 

41We estimate that the approximate margin of error was less than plus or minus 5 

percentage points. 
 

Page 21 GAO-15-38 Pesticide Residue Monitoring

Table 1: Presumptive Tolerance Violation Rates for 10 Selected Commodities, Based on Agricultural Marketing Service (AMS) 

Data, Three Most Recent Years With Data Available for Each Commodity

Commodity

Third most 

recent year in 

which samples 

were taken

Violation rate 

(percentage)

in that year

Second most 

recent year in 

which samples 

were taken

Violation rate 

(percentage)

in that year

Most recent 

year in which 

samples

were taken

Violation rate 

(percentage)

in that year

Apples 2001 0.14% 2004 1.81% 2010 1.34%

Bananas 2002 1.38% 2006 4.45% 2012 0.00%

Broccoli 2001 0.56% 2002 0.41% 2007 4.76%

Cantaloupe 1999 2.53% 2004 0.67% 2011 0.14%

Green beans 2000 1.67% 2004 13.99% 2008 3.10%

Lettuce 2000 0.27% 2005 17.77% 2010 2.96%

Peaches 2001 15.31% 2007 9.19% 2008 9.09%

Pears 1998 19.47% 2004 6.88% 2010 0.94%

Potatoes 2001 1.09% 2002 2.16% 2009 2.28%

Sweet bell peppers 2000 3.52% 2003 3.51% 2010 1.34%

Source: GAO analysis of AMS Pesticide Data Program data. | GAO-15-38

Notes: The data indicate the percentage of samples with at least one violation for each of 3 years—

not necessarily consecutive—from 1998 to 2012. In most instances, samples that AMS reported as 

having presumptive tolerance violations had only one presumptive tolerance violation. Sample sizes 

ranged from 370 for potatoes in 2002 to 831 for cantaloupe in 1999. Most sample sizes were from 

720 to 740 per commodity. The margins of error for the violation rates for all 10 commodities were 

less than plus or minus 5 percentage points.

Although FDA’s monitoring data from 2008 through 2012 show low 

pesticide residue violation rates across the 10 selected commodities we 

examined, FDA’s test results also show that certain foods other than the 

10 selected commodities had relatively high violation rates among the 

samples it tested. For example, in fiscal year 2011 (the most recent year 

for which the agency published its monitoring results), FDA reported 

violation rates among 24 imported food commodities that ranged from 10 

to 75 percent (see table 2).

42 FDA analysis from other recent years also 

found other imported commodities with pesticide residue violation rates of 

at least 10 percent. For example, FDA found 13 such commodities in 

fiscal year 2007, 9 in 2008, 2 in 2009, and 15 in 2010.43

 

42Commodities in this table had at least 20 samples analyzed and a violation rate of 10 

percent or higher or had a minimum of 3 violations and a violation rate of 10 percent or 

higher.

Because FDA 

43FDA published these data in its annual reports on pesticide monitoring. FDA did not 

publish this type of analysis of domestically grown foods.
 

Page 22 GAO-15-38 Pesticide Residue Monitoring

collected these data for the purpose of compliance monitoring and 

enforcement, they represent the rate of violations that the agency 

detected through its targeted testing and are not valid estimates of the 

rate of violations in the foods that FDA regulates as they are not from 

statistically valid random samples. For example, if FDA tested targeted 

samples of apples because of the compliance history of apples, the rate 

of violations in those samples are not valid estimates of the rate of 

violations in all apples.

Table 2: Imported Food Commodities Analyzed by FDA with a Violation Rate of 10 

Percent or Higher, Fiscal Year 2011

Commodity

Targeted samples 

analyzed (number)

Violations 

identified 

(number)

Violation rate 

(percentage)

Ginseng 12 9 75.0%

Capsicums (ground spice) 27 18 66.7%

Prickle pear 11 5 45.5%

Rice, basmati 13 5 38.5%

Raisins 9 3 33.3%

Bok choy 9 3 33.3%

Cilantro 9 3 33.3%

Papaya 69 20 29.0%

Capsicums (whole spice) 32 9 28.1%

Pear 18 5 27.8%

Tea 15 4 26.7%

Tea, chamomile 14 3 21.4%

Spinach 52 9 17.3%

Olives 24 4 16.7%

Serrano pepper 24 4 16.7%

Sweet potato 26 4 15.4%

Tomatillo 31 4 12.9%

Jalapeno pepper 120 15 12.5%

String beans 41 5 12.2%

Blackberries 68 8 11.8%

Red beet 48 5 10.4%

Leek 29 3 10.3%

Choyote 20 2 10.0%

Kale 20 2 10.0%

Source: FDA’s annual report of its 2011 pesticide monitoring program. | GAO-15-38
 

Page 23 GAO-15-38 Pesticide Residue Monitoring

Note: As of June 2014, the most recent year for which FDA had published an annual report 

containing this type of analysis of its test results was 2011. Commodities in this table had at least 20 

samples analyzed and a violation rate of 10 percent or higher or had a minimum of 3 violations and a 

violation rate of 10 percent or higher. Caution should be used when interpreting rates based on a 

small number of samples (i.e., with a small denominator). For example, FDA took nine samples of 

raisins in 2011, and the violation rate of 33.3 percent would have changed by more than 10 

percentage points if FDA had found one violation more or one less in the sample.

According to FDA’s 2011 monitoring report, the commodities identified in 

table 2 may warrant special monitoring attention in the future because of 

the number or percent of violations detected in 2011. FDA also stated in 

its monitoring report that it typically uses multiple years of data as the 

basis for instructing field offices to increase their sampling of commodities 

that have a history of violations. At the same time, FDA noted that its 

pesticide residue monitoring program should not be viewed as random or 

statistical, meaning that the data presented in table 2 are not necessarily 

indicative of actual violation rates for those commodities.

FDA’s current monitoring approach has limitations that affect the agency’s 

ability to detect pesticide residue violations. FDA takes relatively few 

targeted domestic and imported samples to test for pesticide residues. 

Additionally, FDA does not test for several widely used pesticides that 

have established tolerances for many commodities, meaning that it is 

unable to detect violations of those tolerances. Moreover, it is not clear to 

what extent FDA’s recently implemented targeting tool for imported 

foods—PREDICT—helps the agency identify foods most likely to have 

pesticide residue violations.

The number of food samples FDA has tested for pesticide residues in 

recent years has been considerably smaller than what the agency tested 

in the early 1990s. FDA attributes this decrease in targeted samples, at 

least in part, to an increase in its testing for other types of contaminants, 

such as microbiological pathogens. In fiscal year 1993, FDA analyzed 

over 12,000 domestic and imported food samples for pesticide residues. 

That number declined in the subsequent years, reaching a low of about 

5,000 in fiscal year 2008 followed by a small increase as of fiscal year 

2012. Most of that decrease can be attributed to a reduction in the 

number of domestic food samples selected for testing. In the early to mid1990s, FDA tested domestic and imported foods in roughly equal 

numbers. Throughout this period (i.e., fiscal years 1993 through 2012), 

the number of imported samples FDA tested for generally fluctuated from 

about 4,000 to about 7,000, while the number of domestic samples has 

declined from almost 6,000 to less than 1,200 (see fig. 4).

FDA’s Approach for 

Detecting Pesticide 

Residue Violations Has 

Limitations

FDA Takes Relatively Few 

Targeted Samples
 

Page 24 GAO-15-38 Pesticide Residue Monitoring

Figure 4: Total Number of Targeted Samples of Domestic and Imported Foods Tested for Pesticide Residues by FDA, Fiscal 

Years 1993 through 2012

FDA’s targeted samples of imported and domestic foods likely represent 

a very small percentage of all foods that the agency regulates. For 

example, according to agency data for calendar year 2012, FDA tested 

4,600 samples for pesticide residues—less than one-tenth of 1 percent—

of the more than 9.7 million entry lines of imported foods that came 

through U.S. ports.44

 

44An entry line is a unique shipment or lot of a particular food by a particular shipper 

offered for admission into U.S. commerce at a particular place in time. FDA provided us 

data on imported entry lines of foods sampled in calendar year 2012 rather than fiscal 

year 2012 to assist our analysis of the agency’s first full year of using PREDICT. 

This equates to approximately 1 test out of every 

2,100 entry lines. Likewise, FDA’s samples of domestic foods likely 

represent a very small percentage of all domestic foods it regulates. In 

2012, FDA tested 1,167 domestic samples for pesticide residue. 

However, these samples likely represented a smaller proportion of the 

domestic food supply than did the agency’s samples of the imported food 
 

Page 25 GAO-15-38 Pesticide Residue Monitoring

supply for 2012. This is because (1) most of the U.S. food supply is 

domestic and (2) FDA took about one-quarter as many domestic samples 

as imported samples in 2012. According to its recent annual reports, FDA 

has placed a greater emphasis on testing imported foods because it has 

found a higher percentage of imported samples with violations. Because 

FDA’s sampling data are targeted and do not represent all foods that the 

agency regulates, it is not possible to use FDA’s data to estimate how 

much of the foods it regulates contain violative levels of pesticides. As 

described above, however, AMS data (shown in table 1) on the presence 

of presumptive tolerance violations among the 10 commodities we 

reviewed indicate that, for some commodities, the frequency of violations 

that FDA does not detect could be relatively high.

The multiresidue methods FDA uses to test commodities for pesticide 

residues cannot detect all pesticides with established tolerances, 

including six of the most commonly used pesticides in the United States, 

but the agency does not disclose pesticides that it does not test for, 

including these six. FDA is not required by law or regulation to select 

particular commodities for sampling or test for specific pesticides, but best 

practices in survey research, such as practices in OMB standards for 

designing and releasing to the public information concerning a data 

collection effort, call for, among other things, disclosure of conceptual 

limitations that could affect survey results. According to FDA’s 2011 

annual monitoring report, the agency’s testing methods are able to detect 

the majority of the approximately 400 pesticides with established 

tolerances, as well as others without established tolerances, but certain 

commonly used pesticides that have established tolerances must be 

detected using selective residue testing methods that target the particular 

pesticide.45

 

45In its 2011 summary of its monitoring program, FDA reported that it was able to detect 

500 pesticides, including pesticides for which EPA had not established a tolerance. 

Pesticides that have established tolerance levels are registered for use on certain 

commodities.

However, according to FDA officials, the agency does not 

regularly use selective residue testing methods because of their cost. 

Therefore, while there is no requirement that FDA test for all pesticides, 

and increasing the scope of its testing would require additional resources, 

FDA does not know the full extent to which tested commodities comply 

with established tolerances because the agency’s testing methods cannot 

detect all pesticides with tolerances.

FDA Does Not Disclose That It 

Does Not Test for Several 

Commonly Used Pesticides 

with Established Tolerance 

Levels in Foods
 

Page 26 GAO-15-38 Pesticide Residue Monitoring

We identified 6 pesticides that were among the 25 most commonly used 

pesticides in 2001, 2003, 2005, and 2007,46 but that FDA has rarely, if 

ever, tested for in its regulatory monitoring program since 1993 because 

they generally require selective residue testing.47 FDA does not disclose 

in its annual monitoring reports that it does not test for these pesticides. 

These 6 pesticides are glyphosate, 2,4-D, MCPA,48

• Glyphosate: According to a 2011 EPA report, glyphosate was the 

most commonly used agricultural pesticide in the United States in 

2001, 2003, 2005, and 2007. Glyphosate is widely used on several 

major crops, particularly those that have been genetically engineered 

to tolerate it, such as corn and soybeans. EPA has established 

tolerances for glyphosate on over 170 food commodities. An official 

from EPA’s Office of Pesticide Programs said that EPA asked AMS to 

conduct a onetime study of glyphosate residue, despite the costs, 

because FDA was not testing for it, it had widespread use, and likely 

widespread human exposure given the crops for which it was 

registered. Consequently, in 2011, a USDA laboratory tested 300 

soybean samples for glyphosate and its metabolite, 

aminomethylphosphonic acid. USDA detected glyphosate residues in 

about 90 percent of the 300 soybean samples and the glyphosate 

metabolite in over 95 percent of the samples. The largest 

concentration of glyphosate USDA detected was 18.5 parts per 

million; thus, close to but not exceeding the tolerance of 20 parts per 

million. FDA officials cited two reasons FDA does not test for the 

herbicide. First, officials stated that glyphosate levels, if present in 

genetically engineered corn and soybeans, are likely to be reduced by 

the processing done to those foods. Second, according to FDA, the 

total start-up cost to implement selective residue methods for 

glyphosate at its six testing laboratories would be approximately $5 

million. FDA officials stated the agency is evaluating the extent of the 

use of genetically engineered crops for human foods to determine 

mancozeb, paraquat, 

and methyl bromide, all of which are registered for use on food or animal 

feed and have established tolerances.

 

46EPA, Pesticides Industry Sales and Usage: 2006 and 2007 Market Estimates, Biological 

and Economic Analysis Division, Office of Pesticide Programs, Office of Chemical Safety 

and Pollution Prevention, Washington, D.C. 20460 (February 2011). 

47FDA tests commodities for the other 19 most commonly used pesticides. 

48MCPA is an abbreviation for 4-chloro-2-methylphenoxy acetic acid. 
 

Page 27 GAO-15-38 Pesticide Residue Monitoring

whether glyphosate should be added to its pesticide residue 

monitoring program.

• 2,4-D and MCPA: FDA officials stated that, while the agency does not 

test for the pesticides 2,4-D and MCPA in its pesticide monitoring 

program, it does test for them in its Total Diet Study. EPA has 

established tolerances for both pesticides for dozens of food or animal 

feed commodities. According to agency officials, its Total Diet Study 

testing has never detected MCPA, but the agency has detected 2,4-D 

at low levels (below 5 parts per billion) in selected food items. 

However, as has occurred with glyphosate, the use of 2,4-D may 

increase if USDA deregulates the production of corn and soybeans 

genetically engineered to tolerate being sprayed with this herbicide.49

According to FDA officials, testing for 2,4-D would also require a 

selective residue method that would cost approximately $5 million to 

implement throughout its laboratories. FDA officials stated the agency

is evaluating the extent of the use of genetically engineered crops for 

human foods to determine whether 2,4-D should be added to its 

pesticide residue monitoring program. AMS’s Pesticide Data Program 

rarely tested foods for 2,4-D or MCPA from 1998 through 2012.50

• Mancozeb and paraquat: FDA has not tested samples for the 

fungicide mancozeb or the herbicide paraquat, each of which would 

require selective residue testing. In explaining its reasons for not 

testing, FDA said that mancozeb degrades quickly and residues on 

food would likely be very low, and referred to an EPA assessment that 

paraquat posed minimal dietary risk. However, mancozeb has 

established tolerances for over 75 commodities, and paraquat has 

established tolerances for over 110 commodities. AMS’s Pesticide 

Data Program did not test foods for mancozeb or paraquat from 1998 

through 2012.

• Methyl bromide: FDA explained that it does not test for methyl 

bromide because it is a fumigant injected into the soil that dissipates 

or degrades before crops are planted and therefore, no residues 

 

49As of June 2014, USDA was conducting a regulatory review of corn and soybean crops 

engineered to tolerate 2,4-D to determine whether they can be sold without regulation. 

Also, as of June 2014, EPA was conducting risk assessments to decide upon the approval 

of the proposed new uses of 2,4-D.

50AMS tested milk and grapes for 2,4-D and MCPA in 1998 and 2009, respectively. 
 

Page 28 GAO-15-38 Pesticide Residue Monitoring

would be expected in foods. However, methyl bromide also is used on 

crops in postharvest applications, and EPA has established 

tolerances for postharvest uses of the fumigant on about 90 

commodities. AMS’s Pesticide Data Program did not test foods for 

methyl bromide from 1998 through 2012.

Although FDA’s last four annual monitoring reports state that the agency 

tests for the majority of pesticides with established tolerances, the reports 

do not disclose the pesticides with tolerances that the agency does not 

test for in its monitoring program. These annual monitoring reports 

identify the pesticides that the agency is capable of detecting in its 

monitoring program but do not identify which pesticides with tolerances it 

does not test for and the potential effect that not testing for those 

pesticides could have on its detection of violations, namely not detecting 

violations of those pesticides’ tolerances. However, guidance from OMB 

directs agencies to meet certain standards when designing and releasing 

to the public information concerning a data collection effort—such as 

FDA’s pesticide monitoring program—to help ensure and maximize the 

usefulness of information disseminated by the federal government.51

 

51OMB, Standards and Guidelines for Statistical Surveys (September 2006). Although 

FDA’s targeted samples are not intended to produce results with which to generalize, FDA 

uses and reports its targeted sampling data for statistical purposes. For example, it uses 

these data in deciding which future shipments or foods to target for monitoring, and it 

publishes these data in its annual monitoring reports. Therefore, OMB standards about 

presenting results and data are relevant to FDA’s data collection effort. 

For 

example, OMB directs agencies to produce survey documentation that 

includes those materials necessary to understand how to properly 

analyze data from each survey. Without awareness of this limitation (i.e., 

not disclosing the pesticides that have tolerances for which FDA does not 

test), users of the annual monitoring reports may not have accurate 

information and may misinterpret the results of the program, which, by not 

testing for certain pesticides, may be identifying fewer violations than 

occur.
 

Page 29 GAO-15-38 Pesticide Residue Monitoring

Even as it has decreased the scope of its monitoring, in December 2011, 

FDA implemented PREDICT—a tool intended to improve import 

screening and targeting to prevent the entry of adulterated, misbranded, 

or otherwise violative goods. However, after the first full year of use in 

2012, it was not clear what effect the tool has had on FDA’s ability to 

identify foods at high risk of having pesticide residue violations.52

According to FDA officials, the agency’s employees do not rely solely on 

the risk information presented by PREDICT but can use their own 

judgment, or may be directed by FDA headquarters to inspect products 

that do not have high-risk scores.53

PREDICT generates a numerical risk score for each imported entry line 

based on the compliance history of the manufacturer, shipper, importer, 

consignee, and country of origin, as well as inherent health, safety, and 

other product-related variables. PREDICT ranks the risk score relative to 

all other scores generated in the previous 30 days. Entry lines with scores 

that are below the 60th percentile and not otherwise flagged may proceed 

into domestic commerce without further review. Entry lines with scores 

that are at or above the 60th percentile or otherwise flagged are held for 

review for an admissibility decision. An inspector then reviews this 

information, obtains additional documentation, if needed, and decides 

which lines to target for examination or sampling.

According to FDA officials, factors that inspectors consider when deciding 

whether to test a product other than the PREDICT risk score could 

include (1) knowledge of the compliance history of the firm or product that 

is not otherwise captured in the data systems accessed by PREDICT; (2) 

whether FDA had asked districts to target specific products for sampling 

 

52We reported in September 2009 that FDA planned to begin deploying PREDICT on a 

district-by-district basis at all ports and for all FDA-regulated products (e.g., food, drugs, 

and medical devices) in September 2009 over a 6-week period. (See GAO-09-873. In 

March 2012, as part of a review of major FDA data systems, we noted that FDA fully 

deployed PREDICT at the end of December 2011. See GAO, Information Technology: 

FDA Needs to Fully Implement Key Management Practices to Lessen Modernization 

Risks, GAO-12-346 (Washington, D.C.: Mar. 15, 2012).

53According to FDA officials, entry reviewers are FDA employees trained to evaluate 

PREDICT scoring of imported shipments and verify the requirements for FDA-regulated 

products. After conducting the initial entry review, the entry reviewer forwards entries 

selected for further evaluation to the Investigations Branch where FDA inspectors 

coordinate the examination and sampling of selected shipments.

The Effect of FDA’s Targeting 

Tool on the Agency’s Ability to 

Identify Foods at High Risk of 

Pesticide Residue Violations Is 

Unclear
 

Page 30 GAO-15-38 Pesticide Residue Monitoring

based on recent information about a product’s known risk;54 (3) FDA’s 

pesticide program work plan;55

Because FDA’s import sampling decisions are made on the basis of 

multiple sources of information (e.g., the inspector’s judgment or specific 

direction from FDA headquarters) and not simply the PREDICT risk 

score, inspectors may select products for testing that do not have high 

risk scores. In 2012, over 9.7 million imported food entry lines entered the 

country. In general, FDA was more likely to select for testing those entry 

lines that had higher risk scores. For example, FDA tested 0.23 percent of 

the entry lines in the 90th percentile rank versus 0.01 percent of the entry 

lines in the 10th percentile. Overall, however, a cumulative total of about 

25 percent of the entry lines tested in 2012 had risk scores below the 60th 

percentile (see table 3 for details).

(4) staff or equipment availability in the 

district and laboratories; and (5) other relevant information. However, 

FDA officials said that it was impossible to identify each inspector’s 

rationale for selecting each individual product for sampling.

 

54Such direction to districts to target specific products for sampling could include those 

with a high percentage of violations among tested samples in the past, such as targeted 

samples of ginseng, which, as shown in table 2, had a 75 percent violation rate in 2011. 

55In 2009 and 2010, for example, FDA sent to its field offices a domestic and import 

sample collection schedule for the fiscal year. The schedules targeted specific foods, 

farms (for domestic), and countries (for imports) with a known history of illegal pesticide 

residues.
 

Page 31 GAO-15-38 Pesticide Residue Monitoring

Table 3: FDA’s Predictive Risk-based Evaluation for Dynamic Import Compliance Targeting (PREDICT) Scoring for Imported 

Food Entry Lines, Sampling Data, and Violation Rates in 2012

Percentile 

rank Entry lines

Entry 

lines sampled

Cumulative 

percentage

of entry 

lines sampled

Percentage

of entry

lines sampled

Violative

entry lines

Violative entry

lines as a 

percentage

of entry

lines sampled

0-9 2,164,855 214 4.7% 0.01% 9 4.2% 

10-19 1,360,608 204 9.1% 0.01% 11 5.4% 

20-29 1,175,780 193 13.3% 0.02% 18 9.3% 

30-39 1,020,458 165 16.9% 0.02% 10 6.1% 

40-49 772,975 163 20.4% 0.02% 14 8.6% 

50-59 613,174 192 24.6% 0.03% 23 12.0%

60-69 723,304 614 38.0% 0.09% 43 7.0% 

70-79 981,812 1,102 61.9% 0.11% 99 9.0% 

80-89 409,475 577 74.4% 0.14% 43 7.5% 

90-100 503,616 1,171 99.9% 0.23% 132 11.3%

No score 21,896 a 5 100.0% 0.02% 3 60.0%

Total

b

9,747,953 4,600 100.0% 0.05% 405 8.8% 

Source: GAO analysis of FDA data. | GAO-15-38

Note: An entry line is a unique shipment of imported products or items offered for admission into U.S. 

commerce.

a

FDA did not have PREDICT scores for all entry lines of imported foods in 2012.

b

Rates based on a small number of samples (i.e., with a small denominator) may be less precise than 

rates based on a large number of samples. The percentile rank category of “no score” had five 

samples, and the violation rate of 60 percent would have changed by more than 20 percent if FDA 

had found one more or one less violation.

FDA’s test results from 2012 show that, in some instances, the decisions 

of inspectors to test entry lines that had low-risk scores were justified 

when the agency found violations. However, high violation rates did not 

necessarily correspond with high-risk scores generated by PREDICT 

among the entry lines that FDA tested. FDA took a total of 4,600 samples 

of imported food entry lines in 2012, of which 405, or 8.8 percent, were 

violative because they contained pesticide residues in excess of 

established tolerance levels or for which no tolerance had been 

established. Although results cannot be generalized beyond FDA’s 

PREDICT sample without a statistically valid, representative sample and 

it is difficult to reliably assess the relationship between PREDICT scores 

and violation rates without such a sample and, while this was the first 

year of PREDICT’s implementation, FDA data show an inconsistent 

relationship between PREDICT scores and violation rates among the 
 

Page 32 GAO-15-38 Pesticide Residue Monitoring

sample of shipments that were tested. As depicted in table 3, the entry 

lines with the highest violation rate (12.0 percent) had risk scores in the 

50th to 59th percentile and entry lines with the third highest violation rate 

(9.3 percent) had scores in the 20th to 29th percentile. Entry lines with 

risk scores in the 90th to 100th percentile had the second highest 

violation rate (11.3 percent). FDA data further show that the samples the 

agency tested with PREDICT scores below the 60th percentile had an 

overall violation rate (7.5 percent)56 that was similar to the rate for entry 

lines with scores at or above the 60th percentile (9.2 percent).57

In addition, FDA did not test the vast majority of entry lines that had the 

highest PREDICT risk scores. In 2012, over 2.6 million entry lines scored 

above the 60th percentile, meaning that there was enough concern about 

these lines that FDA did not automatically allow them to proceed into 

commerce. Of those, FDA tested samples from 3,464 and did not test 

more than 500,000 of the 503,616 entry lines that had risk scores in the 

90th to 100th percentile. This indicates that even if a system such as 

PREDICT is able to accurately identify high-risk foods, FDA’s monitoring 

program is only capable of testing a small percentage of those foods for 

violations. FDA acknowledges that it is able to physically examine only a 

small percentage of imports and states that it is essential that screening 

and targeting be as effective as possible.

This 

could suggest that PREDICT inconsistently identified entry lines with 

violations or it could suggest that factors other than PREDICT caused the 

agency to test entry lines that were at risk of a violation in spite of their 

lower PREDICT scores, or both. To reliably assess the effectiveness of 

PREDICT, therefore, the agency would need a statistically valid, 

representative sample of entry lines.

All 4,600 of the samples FDA tested in 2012 could have been selected 

from the more than 500,000 entry lines with a PREDICT risk score in the 

90th to 100th percentile. However, FDA officials stated that there are 

several practical reasons why an inspector may not physically inspect and 

test a particular product falling within the highest percentile rank. For 

 

56The overall violation rate for entry lines below the 60th percentile (7.5) is found by 

dividing the total number of violations (85) by the total number of entry lines sampled 

(1,131).

57The overall violation rate for entry lines in the 60th percentile and above (9.2) is found by 

dividing the total number of violations (317) by the total number of entry lines sampled 

(3,464). 
 

Page 33 GAO-15-38 Pesticide Residue Monitoring

example, a perishable product might cross a port of entry that temporarily 

lacks an available inspector. In addition, an inspector may not test a 

product with the highest percentile rank if the product already was subject 

to an Import Alert and could be detained without physical examination, or 

because the district recently tested a shipment of the same product from 

the same grower and found no violations. According to FDA officials, 

constraints on inspection staff and laboratory resources may also affect 

whether a product is tested.

FDA officials said that they were aware of the inconsistent relationship 

between PREDICT scores and detected violations in 2012 and were 

examining the issue in an ongoing, systemwide evaluation of PREDICT. 

In early 2013, FDA began an internal evaluation of PREDICT’s overall 

effectiveness at identifying high-risk imported products; that effort was still 

ongoing as of July 2014. However, FDA’s evaluation of PREDICT’s 

effectiveness at targeting violative food products is hindered without 

having a statistically valid sample of foods that FDA regulates and that 

would serve as a baseline with which to compare PREDICT’s results. 

OMB’s standards on the professional principles and practices that federal 

agencies are directed to adhere to in all statistical activities58 state that 

agencies must use generally accepted statistical methods, such as a 

probabilistic method that can provide estimates of sampling error, or 

justify statistically a nonprobability method that can measure the 

estimation error.59

 

58OMB, Standards and Guidelines for Statistical Surveys (September 2006). In part, this 

guidance directs that agency survey designs use generally accepted statistical methods, 

such as probabilistic methods that can provide estimates of sampling error. Any use of 

nonprobability sampling methods must be justified statistically and be able to measure 

estimation error. 

FDA’s written plan for conducting its evaluation of 

PREDICT does not call for the agency to collect a statistically valid 

sample on the frequency of pesticide residue violations or provide the 

requisite justification. As discussed later in this report, according to FDA 

officials, calculating national estimates of pesticide violations for the entire 

food supply it regulates would be very expensive. However, without a 

statistically valid sample that would enable the agency to assess the 

reliability of PREDICT risk scores to indicate the presence of violations, 

FDA cannot derive a reliable estimate of the rate at which PREDICT is 

59According to the OMB standards, the size and design of the sample must reflect the 

level of detail needed in tabulations and other data products, and the precision required of 

key estimates. 
 

Page 34 GAO-15-38 Pesticide Residue Monitoring

effectively identifying imported foods that contain violative levels of 

pesticide residues. Furthermore, because FDA uses PREDICT to identify 

risks among a wide range of products—not limited to foods—it is not clear 

the extent to which the scope of FDA’s evaluation will enable it to address 

the effectiveness of PREDICT regarding pesticides specifically.

In addition to the limitations in FDA’s risk-based, targeted compliance and 

enforcement monitoring described above, FDA’s monitoring program 

focuses on testing foods that have been targeted as part of monitoring for 

compliance and enforcement to the exclusion of determining the 

incidence and level of pesticide residues in domestic and imported foods. 

However, according to FDA’s Compliance Program Guidance Manual, 

another of the agency’s objectives is to determine the incidence and level 

of pesticide residues in domestic and imported foods. As we stated 

earlier, OMB standards provide guidance to agencies seeking to make 

estimates about populations, such as the incidence and level of pesticide 

residues in food.60 Those standards state that agencies must select 

samples using generally accepted statistical methods, such as methods 

of probability sampling that can provide estimates of sampling error,61

 

60OMB, Standards and Guidelines for Statistical Surveys (September 2006).

and 

any method that uses nonprobability sampling must be justified 

statistically and be able to measure estimation error. In addition, the size 

and design of the survey must reflect the precision required of key 

estimates. The OMB standards also address how agencies are to release 

information to the public, including information on limitations in the survey 

methodology. Determining the sufficient size and design of the sample 

would depend on what FDA wanted to know. If, for example, the agency 

wanted to know incidence and level of pesticide residues across all 

domestic and imported foods, it would need to design statistically valid 

random samples of those two broad categories of foods. If, on the other 

hand, FDA wanted to know about residue levels within particular 

commodities, it would need to design a survey of random samples of 

those commodities that meets statistical standards. FDA is not currently 

taking either of these approaches in its regulatory monitoring program. 

Finally, FDA’s ability to evaluate the effectiveness of its targeted 

61Sampling error refers to the variation in estimates from sample to sample due to 

sampling alone. Sampling error can often be reduced by drawing larger samples or using 

efficient sample design and analytical methods.

FDA Does Not Use 

Statistically Valid Methods 

to Gather Residue 

Incidence and Level Data 

for Its Pesticide Monitoring 

Program
 

Page 35 GAO-15-38 Pesticide Residue Monitoring

monitoring program (i.e., enforce pesticide residue tolerances in foods 

established by EPA) is limited because it has not determined the 

incidence and level of pesticide residues in the foods it regulates against 

which it can compare the results of its targeted compliance and 

enforcement monitoring.

In the early 1990s, FDA used statistically based samples of apples, 

pears, rice, and tomatoes to estimate the incidence and level of pesticide 

residues in those commodities. In each case, the agency took over 1,200 

samples covering domestic and imported sources of the four 

commodities. Recent annual FDA monitoring reports indicate that the

agency has not repeated this type of analysis because of resource 

constraints. In addition, to produce estimates for specific commodities in 

which it could be 95 percent confident, FDA documents have stated that 

the agency would need at least 800 imported and 800 domestic samples 

of each. Without designing and implementing a statistically valid sampling 

approach that would enable it to gather nationally representative 

incidence and level data for both domestically produced and imported 

foods, FDA is less able to determine the safety of the U.S. food supply 

and provide the users of its annual pesticide monitoring reports with 

reliable national estimates of the rate at which foods FDA regulates 

contain violative levels of pesticides. FDA officials said that calculating 

national estimates for the entire food supply it regulates would be very 

expensive because it would require a large number of samples for a wide 

array of products. The officials, however, did not provide estimates or 

documentation on the cost of a statistically valid sampling approach or 

whether they had assessed the trade-offs of doing less risk-based 

targeting and more random sampling.

FDA’s focus on testing commodities that have been targeted as part of 

monitoring for compliance and enforcement to the exclusion of 

determining the incidence and level of pesticide residues in domestic and 

imported foods limits the agency’s ability to make valid statements about 

violation rates for domestic and imported foods. FDA has stated in annual 

monitoring reports that imported foods it tested were more likely to have 

pesticide residue violations than domestic foods it tested. For example, in 

its summary of fiscal year 2011 test data, FDA stated that it found 

violative residues in 7.1 percent of the imported products it tested and 1.6 

percent of the domestic products. For fiscal year 2010, FDA reported 

violative residues in 4.9 percent of imported products it tested and 1.9 

percent of domestic products, and the rates were 4.0 and 1.4 for imported 

and domestic products it tested, respectively, in fiscal year 2009. FDA 

also reported the violation rates it found within certain categories of food; 
 

Page 36 GAO-15-38 Pesticide Residue Monitoring

namely, grains, fruits, vegetables, dairy, fish, and “other.” For example, in 

2011, FDA stated that the violation rate for domestic fruits it tested was 

2.4 percent, and the rate for imported fruits was 6.9 percent. In making 

these statements, FDA considered both types of violations—those in 

which an established tolerance was exceeded and those in which a 

pesticide without an established tolerance was detected.

Determining whether these differences in violation rates represent 

underlying differences between domestic and imported commodities, 

however, is complicated by the fact that FDA does not collect data on 

violations using statistically valid samples, as described above. Therefore, 

based on standard statistical principles, it would not be valid or reliable to 

infer from the data that FDA collects through its targeted monitoring that 

imported commodities are more violative overall. These statistical 

principles suggest that it would be more valid to compare violation rates 

for a given commodity for imports to the same commodity for domestics—

that is, an apples-to-apples comparison if violation rates are suspected to 

differ by commodity. Regardless, such a comparison would examine 

domestic and imported samples, whether by commodity or overall, 

selected in a statistically valid manner with sample sizes that are large 

enough and balanced enough to yield high levels of statistical confidence. 

The relatively small number of samples taken by FDA’s monitoring 

program means that few, if any, commodities meet the sample size 

criteria in a single year, and no commodities were selected in the 

statistically valid method described above.

FDA’s ability to evaluate how effectively its monitoring program detects 

and intercepts violative foods is also limited by the fact that it does not 

gather incidence and level data in a statistically valid manner, but only 

through a targeted sampling approach. The control activities standard 

under the federal standards for internal control call for agency 

management at the functional or activity level to compare actual 

performance with planned or expected results and analyze significant 

differences.62

 

62GAO, Standards for Internal Control in the Federal Government, 

However, as discussed, FDA’s pesticide monitoring 

program does not collect nationally representative data on the overall or 

commodity level rate of pesticide residue violations within the domestic 

and imported food supplies. As a result, FDA does not have

GAO/AIMD-00-21.3.1

(Washington, D.C.: November 1999). 
 

Page 37 GAO-15-38 Pesticide Residue Monitoring

representative data on such violations with which to compare the rate of 

violations detected through targeted pesticide monitoring. Depending on 

its level of precision, nationally representative data could also help FDA 

identify domestic or imported foods that are at a high risk of violating 

pesticide tolerances.

In addition to its targeted pesticide monitoring program, according to FDA 

reports, there are two sources of data on the overall incidence and level 

of pesticide residue in foods that FDA can use to quantify the presence of 

pesticide residue violations. However, these sources—FDA’s Total Diet 

Study and AMS’s Pesticide Data Program—have characteristics that 

affect their use in evaluating the effectiveness of FDA’s targeted pesticide 

monitoring program. According to FDA, by its design, the Total Diet Study 

serves as an early warning system and is capable of detecting many 

more pesticide residues and at much greater sensitivity when compared 

with FDA’s regulatory monitoring program. FDA’s reports also state the 

agency relies on data from the Pesticide Data Program, which collects 

residue data on 20 to 30 commodities every year, with an emphasis on 

highly consumed commodities. Through December 2013, the program 

had gathered data on more than 90 commodities. And, in comparison to 

FDA’s regulatory monitoring program, AMS’s Pesticide Data Program is 

able to take considerably larger sample sizes.

While these two sources of data can help FDA identify emerging pesticide 

residue problems, because of their sampling methodologies, neither study 

can be used to directly and reliably evaluate the effectiveness of FDA’s 

monitoring program across the domestic and imported food supplies. 

Although the Total Diet Study takes samples from a wide range of foods 

(i.e., over 270 different items composited from samples collected from 

three different cities), each study is only conducted four times each year. 

Therefore, specific foods are sampled only four times per year. The 

Pesticide Data Program tests large sample sizes but takes samples from 

relatively few commodities each year. In addition, both studies may first 

wash or peel foods before testing, simulating typical consumer handling. 

The Total Diet Study cooks some foods, including prepared foods 

containing multiple ingredients. These steps could reduce the detected 

concentration of pesticides. Without representative data on the presence 

of pesticide residue violations throughout the food supply, FDA cannot 

reliably evaluate the extent to which its monitoring program detects and 

intercepts violations at a rate greater than random chance.
 

Page 38 GAO-15-38 Pesticide Residue Monitoring

Data from FSIS’s National Residue Program for meat, poultry, and egg 

products (animal products) show a low rate of pesticide residue violations 

from 2000 through 2011. However, FSIS’s approach for detecting 

violations during that period had limitations because the agency did not 

test these products for all pesticides with an established tolerance, and 

FSIS did not disclose those limitations in its annual pesticide monitoring 

reports. In addition, over that period, FSIS reduced the frequency with 

which it tested animal products for residues, a reduction in both the 

number of samples taken in a particular year and in the types of animal 

products tested. In 2011, in response to a USDA Office of Inspector 

General report, FSIS increased the number of pesticides that it tests for. 

In addition, according to agency officials, FSIS and EPA reached an 

informal agreement in May 2014 on changes to the National Residue 

Program that the agencies expect will make the data for residues in beef, 

pork, and poultry more useful for EPA in assessing potential dietary 

exposure and in determining pesticide risks to human health.

FSIS found a total of 30 pesticide residue violations out of nearly 55,000 

random samples of domestic and imported meat, poultry, and processed 

egg products from 2000 through 2011.63 In 3 of the 12 years we reviewed, 

FSIS found no pesticide violations, while in the other 9 years, it found 

from 1 to 8 violations. In each year in which it found violations, FSIS 

found them in far less than 1 percent of the animal products it tested. The 

30 violations that FSIS found were distributed across 12 types of animal 

products known as production classes.64

 

63All but 3 of the pesticide violations were in domestic products. The National Residue 

Program also occasionally found violations for other environmental contaminants, such as 

fire retardants, during this time period. In addition, the program found violative amounts of 

animal drugs such as antibiotics.

The production class with the 

greatest number of violations was boars/stags, with 13 violations for five 

different pesticides. All other production classes had 2 or fewer violations.

64Overall, FSIS tested 28 animal product types, or production classes; each production 

class was tested at least once during the period 2000 through 2011. They include horses, 

bulls, beef cows, dairy cows, heifers, steers, bison, bob veal, formula-fed veal, nonformula-fed veal, heavy calves, mature sheep, lambs, goats, market hogs, boars/stags, 

sows, roaster pigs, young chickens, mature chickens, young turkeys, mature turkeys, 

ducks, geese, ratites (which include ostrich and emu), squabs, rabbits, and processed egg 

products.

FSIS Data for 2000 

through 2011 Show 

Low Pesticide 

Residue Violation 

Rates for Meat, 

Poultry, and 

Processed Egg 

Products, but FSIS 

Did Not Disclose 

Limitations in the 

Data

FSIS’s National Residue 

Program Data for 2000 

through 2011 Showed Low 

Violation Rates in Meat, 

Poultry, and Processed 

Egg Products, but 

Limitations in Its Data Are 

Not Disclosed
 

Page 39 GAO-15-38 Pesticide Residue Monitoring

The 30 violations covered 14 separate pesticides for which FSIS found 

residues that either exceeded established tolerances or for which EPA 

had not established a tolerance.65 The most common violation, which 

FSIS found six times, was for hexachlorobenzene.66 According to EPA 

documents, hexachlorobenzene is no longer used but was commonly 

used into the 1960s as a pesticide, a fungicide, and for certain industrial 

purposes. It is still found in animal products because of its persistence in 

the environment. FSIS found other residue violations from 1 to 4 times 

from 2000 through 2011, including for the pesticides DDT67

FSIS also detected pesticides in some domestic and imported samples at 

levels that did not exceed established tolerances. The percentage of 

domestic samples with nonviolative detections declined over the time 

period we examined, from about 7 percent of about 7,500 samples in 

2000 to 0.2 percent of about 1,900 samples taken in 2011. For imported 

samples, the percentage with nonviolative detections also declined, from 

about 6 percent of about 750 samples taken in 2001 to no detections in 

about 300 samples taken in 2011. The pesticide most frequently detected 

at nonviolative levels or below action levels was DDT. For example, in 

2000, 371 of the 490 nonviolative detections in domestic products were of 

DDT. The decline in the rate of detections of pesticides at nonviolative or 

below action levels over this time period could be attributed to the 

and chlordane 

that have been banned from use in the United States for about 40 years 

and 25 years, respectively, but are known to persist in the environment 

and can accumulate in plants ingested by animals. Although banned in 

the United States, DDT and chlordane may be used in other countries 

and, thus, have the potential to be in imported foods. While there is no 

EPA-established tolerance for DDT, EPA recommended an “action level” 

of 5 parts per million. EPA recommended an action level of 0.3 parts per 

million for chlordane. FSIS does not permit residues of DDT or chlordane 

above those levels.

 

65Seven of the 30 violations exceeded established tolerances, and 22 were violations for 

which there was no established tolerance. One violation was for a pesticide identified by 

FSIS as a “chlorinated hydrocarbon.” That term denotes a family of pesticides. We were 

not able to determine the specific name of the pesticide or whether it had an established 

tolerance.

66The other 13 named pesticides FSIS found at violative levels were carbaryl, chlordane, 

chlorfenvinphos, coumaphos, DDT, dieldrin, ethion, heptachlor, lindane, methoxychlor, 

mirex, permethrin, and piperonyl butoxide.

67DDT is the abbreviation for dichloro-diphenyl-trichloroethane.
 

Page 40 GAO-15-38 Pesticide Residue Monitoring

possibility that persistent, but no longer used, pesticides such as DDT are 

less present in the environment. However, FSIS’s approach may have 

underestimated violations from 2000 through 2011 as the agency (1) did 

not test meat, poultry, and processed egg products for all pesticides with 

established tolerance levels and (2) generally reduced the animal 

production classes tested for pesticide residue.

While FSIS’s National Residue Program found relatively few pesticide 

tolerance violations from 2000 through 2011, its multiresidue testing 

method did not test meat, poultry, and processed egg products for all 

pesticides that had an established EPA tolerance. Therefore, the 

pesticides it tested for did not represent the full range of pesticides that 

might come in contact with meat, poultry, and processed egg products 

through direct application or through animal feed. In addition, FSIS’s 

annual reports did not identify which pesticides with tolerances were not 

covered by the testing program.

According to FSIS documents, from 2000 through 2010, the agency 

increased its testing from about 20 to about 42 pesticides each year. In 

2011, FSIS’s guidance for its pesticide testing program called for a further 

increase to 55 pesticides. According to FSIS officials, the agency 

increased the number of pesticides it tested for in response to a 

recommendation in a 2010 report by USDA’s Office of Inspector 

General68 and requests from EPA’s Office of Pesticide Programs. With 

the increase, FSIS tested for 9 of the 18 pesticides that are registered for 

direct use on food animals (see table 4). 

 

68FSIS National Residue Program for Cattle, USDA Office of Inspector General, Audit 

Report 24601-08-KC (Mar. 25, 2010).

FSIS’s National Residue 

Program Did Not Test Meat, 

Poultry, and Processed Egg 

Products for All Pesticides with 

Established Tolerance Levels
 

Page 41 GAO-15-38 Pesticide Residue Monitoring

Table 4: Pesticides with Tolerances for Direct Use on Food Animals in the Food 

Safety and Inspection Service’s (FSIS) August 2011, Pesticide Testing Guidance

Name of pesticide with established

tolerance and registered for direct use on food animals

Included in FSIS’s 

2011 guidance for 

pesticide testing

Abamectin No

Amitraz No

Carbaryl Yes

Chlorpyrifos Yes

Coumaphos No

Cyfluthrin No

Cypermethrin Yes

Diazinon No

Dichlorvos Yes

Diflubenzuron Yes

Endosulfan Yes

Lambda-Cyhalothrin Yes

Malathion No

Permethrin Yes

Phosmet No

Piperonyl butoxide Yes

Pirimiphos-methyl No

Pyrethrins No

Sources: GAO analysis of EPA and FSIS documents. | GAO-15-38

Note: The pesticides in this table were registered by EPA for direct animal use as of February 2014.

In total, FSIS’s 2011 program tested for 38 of the 191 pesticides that have 

established tolerances for both direct and indirect use on animals. In 

addition, FSIS tested for 17 pesticides that do not have established 

tolerances in animal products, bringing the number in its testing program 

to 55. The 17 pesticides without tolerances include some that may have 

been used in the past but now are banned or restricted in the United 

States. As of February 2014, there were 191 pesticides for which EPA 

had established residue tolerances in meat, poultry, and processed egg 

products, including 18 pesticides that are registered for direct use on 
 

Page 42 GAO-15-38 Pesticide Residue Monitoring

animals that produce these foods.69

As is the case with FDA, FSIS is not required by law or regulation to test 

the foods it samples for specific pesticides. However, OMB’s standards 

for designing and releasing to the public information concerning a data 

collection effort also apply to FSIS’s National Residue Program. In that 

regard, FSIS’s annual reports do not meet OMB’s best practices for 

statistical surveys because the agency does not disclose the pesticides 

with tolerances for which it does not test or the potential effect that its 

selection of pesticides could have on its results. Similarly, FSIS does not 

disclose the potential bias associated with its selection of production 

classes for testing. Such disclosure would be consistent with OMB 

standards for reporting limitations relevant to a data collection effort. By 

not providing this information, FSIS does not disclose conceptual 

limitations associated with its survey. Without information on these 

limitations and measures of sampling error (margin of error), users of the 

agency’s annual monitoring reports may not have accurate information 

and may misinterpret the results of the program, which is identifying fewer 

violations for meat, poultry, and processed egg products than could 

occur.

Other pesticides are registered for 

use on animal feed, and EPA has established tolerances for the meat, 

poultry, and processed egg products of the animals that might consume 

that feed.

 

69We did not attempt to determine the number and identity of each pesticide with 

established EPA tolerances for meat, poultry, and processed egg products in each year 

from 2000 through 2011. Instead, we performed our analysis using data on tolerances 

from February 2014 and acknowledge that the more recent data may include pesticides 

with tolerances that were established after 2011. We requested help from EPA in 

identifying pesticides with established tolerances for animal products. In turn, EPA 

requested that a contractor that manages data on registered pesticides query its database 

to provide information on tolerances as of February 2014. We determined that it would be 

unreasonably burdensome to request that the contractor also search for tolerances 

established for animal products for each year from 2000 through 2011. The data do not 

account for pesticides with EPA established tolerances for goat or horse products. After 

reviewing EPA tolerance regulations, we found that there were no pesticides with 

tolerances for goat or horse that did not also have a tolerance for another animal product. 

In light of that information, we did not request a separate query for goat or horse products.
 

Page 43 GAO-15-38 Pesticide Residue Monitoring

In light of other priorities, from 2000 through 2009, FSIS reduced the 

number of domestic and imported samples taken from over 8,000 per 

year to less than 1,900 before increasing samples to more than 2,100 in 

2010 and 2011.70

From 2000 through 2005, the agency tested as few as 19 to as many as 

28 domestic production classes per year. However, from 2006 through 

2011, FSIS tested 7 to 10 production classes per year. In addition, FSIS 

has not tested several production classes for pesticides for many years. 

For example, it has not tested ducks, geese, ratites (e.g., ostrich and 

emu), squabs, or rabbits since 2003, or young and mature turkeys and 

processed egg products since 2005. For the most part, the total U.S. 

consumption of these production classes is small; FSIS reports that all 

but young turkeys and processed egg products were each less than 1 

percent of total meat, poultry, and processed egg products consumed in 

2011.

The number of samples that FSIS tests of a particular 

production class affects the precision with which it can project its results 

across all of that class. According to FSIS annual reports, in 2006, the 

agency’s goal was to test 230 to 300 samples from each production class 

to obtain results that were statistically meaningful. These reports indicate 

that testing sample sizes of 230 or 300 ensured FSIS a 90 percent or 95 

percent probability, respectively, of detecting chemical residue violations 

if the violation rate is equal to or greater than 1 percent in the population 

being sampled. From 2006 through 2011, even with the general decline in 

the overall number of samples, FSIS’s sample sizes for each production 

class tested generally exceeded 230. While FSIS did not decrease the 

sample size per production class, it did reduce the number of production 

classes it sampled. This led to a reduction in the total number of samples 

per year.

71

 

70FSIS continued to increase the number of samples it took after 2011, the end point of 

our analysis of violation data. In 2012, FSIS stated in its Residue Sampling Plan that it 

would increase its goal to 800 samples for each production class tested. FSIS explained 

that, by increasing the number of samples taken, it would increase its probability of finding 

a violation to greater than 99 percent, if the violation rate was equal to or greater than 1 

percent in the population being sampled. In 2013, FSIS’s 5,900 samples were spread 

across nine production classes, for an average of 656 per class, or about 144 less than its 

target of 800. FSIS officials said that to increase its sample size for each production class, 

the agency would have to decrease the number of production classes sampled in any 1 

year. 

As we said earlier, according to FSIS officials, in 2011 the agency 

71Young turkeys were about 5.2 percent, and processed egg products were about 4.7 

percent of total meat, poultry, and processed egg products consumed in 2011, according 

to FSIS. 

From 2000 through 2011, FSIS 

Generally Reduced the 

Number of Samples and 

Animal Production Classes 

Tested for Pesticide Residue
 

Page 44 GAO-15-38 Pesticide Residue Monitoring

increased the number of pesticides it tested for in response to a 

recommendation in a 2010 report by USDA’s Office of Inspector General 

and requests from EPA’s Office of Pesticide Programs.

FSIS has recently engaged with EPA on three types of changes to the 

National Residue Program that would enhance FSIS’s collection and 

reporting of residue data. In addition to FSIS’s use of the program’s data 

for enforcing tolerances, EPA uses the data to assess potential dietary 

exposure in determining pesticide risks to human health. EPA also has 

used data on such residues in beef, pork, and poultry from AMS’s 

Pesticide Data Program. However, AMS decided in 2012 to stop testing 

these commodities for pesticides, and EPA officials were concerned that 

FSIS’s monitoring data would not be able to replace the AMS data and 

serve EPA’s purposes.72

 

72According to the former Director of the Pesticide Data Program, AMS decided to stop 

testing meat and poultry samples (it had never tested processed egg products) after FSIS 

issued a Federal Register notice in July 2012, announcing its plan to modify and expand 

the National Residue Program. Specifically, FSIS announced it would begin using several 

multiresidue methods for analyzing samples for residues, including pesticide residues. 

According to the Director, it would be duplicative for both AMS and FSIS to conduct 

residue testing on meat and poultry using similar multiresidue methods, particularly as 

AMS does not have the authority to enter meat processing plants and had to rely on FSIS 

to obtain samples. The Director also noted that funding constraints led AMS to reduce the 

scope of the Pesticide Data Program by discontinuing its testing of meat and poultry. 

Specifically, according to the Chief of EPA’s 

chemistry and exposure branch, AMS’s Pesticide Data Program (1) 

tested for a broader array of pesticides than FSIS has tested for in its 

National Residue Program, (2) was able to detect lower concentrations of 

the pesticides it tested for than FSIS has, and (3) made its data available 

to EPA in a more detailed format and in a timelier manner than FSIS has 

in its annual reports. Since AMS’s decision that it would no longer include 

beef, pork, or poultry in its Pesticide Data Program, EPA has engaged in 

discussions with FSIS about ways that FSIS could enhance its National 

Residue Program to address these issues. Through these discussions, 

EPA and FSIS officials said they had reached some agreement 

concerning the pesticides for which FSIS tests, the residue detection 

levels FSIS can achieve, and the format and timing of the FSIS data as 

discussed below.

FSIS Has Engaged with 

EPA on Changes to the 

National Residue Program
 

Page 45 GAO-15-38 Pesticide Residue Monitoring

As reported in 2010 by USDA’s Office of Inspector General and described 

to us by EPA officials, EPA has for years urged FSIS to increase the 

number of pesticides included in FSIS’s National Residue Program.73

Most recently, in April 2014, EPA provided FSIS with a document 

containing a list of 207 pesticides that AMS’s Pesticide Data Program had 

tested for in beef, pork, and poultry but for which FSIS did not necessarily 

test in its National Residue Program. In the document, EPA indicated its 

priorities for which pesticides FSIS should include in its residue program. 

According to the EPA document, the agency used several criteria to 

develop its list of priorities, including whether AMS had previously 

detected these pesticides in samples and a measure of a pesticide’s 

tendency to accumulate in fat. In May 2014, EPA and FSIS officials said 

they had reached agreement about the status of specific pesticides 

contained in EPA’s priority list, such as whether FSIS tested for a specific 

pesticide or was in the process of adding this pesticide to its testing 

program. To add pesticides, FSIS must determine that its equipment is 

capable of detecting and accurately measuring individual pesticides in 

different types of animal tissue. According to the executive associate of 

FSIS’s laboratories, the agency completed the process of validating the 

method needed to test for 88 pesticides in June 2014, and the agency’s 

updated program guidance went into effect in July 2014. With that update 

to its program, as of July 2014, FSIS either tested or, according to agency 

program guidance, planned to start testing in July 2014 for 85 of the 207 

pesticides on EPA’s priority list.74

 

73FSIS National Residue Program for Cattle, USDA Office of Inspector General, Audit 

Report 24601-08-KC (Mar. 25, 2010). 

However, as shown in table 5, many of 

the pesticides considered a priority by EPA are not in FSIS’s current or 

planned testing program. For example, 13 of EPA’s 32 “highest” priority 

and 27 of EPA’s 41 “high” priority pesticides are not included. The Chief 

of EPA’s chemistry and exposure branch in the Office of Pesticide 

Programs said that while he does not necessarily expect to see 

significantly more pesticide residue violations as a result of the expanded 

testing, data on additional pesticides—whether it shows the presence of 

residues or not—would help EPA refine its risk assessments. According 

to officials from both agencies, FSIS and EPA will continue to discuss 

how their priorities can be met with existing resource limitations.

74According to FSIS’s program guidance, the agency will test for three pesticides that are 

not on EPA’s priority list, bringing the total number tested for to 88. 

Number of Pesticides for 

Which FSIS Tests
 

Page 46 GAO-15-38 Pesticide Residue Monitoring

Table 5: Pesticides Tested for in Beef, Pork, and Poultry Included, or Planned for 

Inclusion, in the Food Safety and Inspection Service’s (FSIS) National Residue 

Program, as of July 2014

EPA’s 

priority

Pesticides in EPA’s 

2014 priority list

Pesticides in

EPA’s priority list

planned for FSIS’s 

National Residue

Program in July 2014

Pesticides in EPA’s 

2014 priority list

but not planned for

FSIS’s 2014 National

Residue Program

Highest 32 19 13

High 41 14 27

Medium 51 17 34

Low 83 35 48

Total 207 85 122

Sources: EPA and FSIS data. | GAO-15-38

Note: According to FSIS’s testing guidance, its testing program will include three pesticides that were 

not included in the Agricultural Marketing Service’s Pesticide Data Program and, as a result, were not 

included in EPA’s list of priorities.

In addition to discussing with FSIS the list of pesticides to include in the 

National Residue Program, EPA also has discussed changes in the limits 

of detection that FSIS can achieve for those pesticides. The executive 

associate of FSIS’s laboratories said that because the agency’s objective 

is to identify residue violations, rather than gather residue exposure data, 

it is not necessary that its testing methods be able to detect residues at 

levels well below the established tolerances. FSIS uses the term 

“minimum level of applicability” to refer to the lowest residue 

concentration that has been validated to be accurately and consistently 

reported by its testing method in a type of animal product. According to 

the executive associate, if a pesticide has an established tolerance, FSIS 

typically sets the minimum level of applicability at one-half of the 

tolerance. If there is no tolerance for a pesticide, FSIS sets the minimum 

level of applicability at five times the level of quantitation, which is the 

lowest concentration that its equipment can reliably measure. According 

to the Chief of EPA’s chemistry and exposure branch, EPA expressed its 

concerns to FSIS that the relatively high FSIS minimum levels of 

applicability hampered EPA’s ability to accurately estimate exposure to 

pesticide residues in food. That is because, according to the branch 

Chief, when FSIS reports that it did not detect any residue of a particular 

pesticide, EPA’s practice has been to assume that the tested commodity 

had residue equaling one-half of the minimum level of applicability rather 

than no residue. To improve the precision of its risk assessments, EPA 

asked FSIS in August 2013 if it could lower its minimum level of 

applicability to one-tenth of the tolerance level for those pesticides that 

Residue Detection Limits FSIS 

Can Achieve
 

Page 47 GAO-15-38 Pesticide Residue Monitoring

have a tolerance for meat or poultry. However, in May 2014, the EPA 

branch Chief said that, after further review of FSIS’s testing capabilities, 

EPA determined that, for the most part, FSIS’s current minimum levels of 

applicability are adequate to meet EPA’s needs. Further, according to 

agency officials, FSIS has agreed that, as its resources permit, it will look 

for ways to lower minimum levels of applicability on a case-by-case basis.

According to the Chief of EPA’s chemistry and exposure branch, EPA’s 

Office of Pesticide Programs wants to use FSIS data in its pesticide risk 

assessments but would need FSIS to make the data available to EPA in a 

more detailed format; in the past, the official said that EPA only received 

summary data from FSIS that were not adequate for its risk assessments. 

When EPA conducts risk assessments, according to the official, it must 

also make its source data fully available so that the public can review and 

analyze them. However, FSIS has not been making its source data 

similarly available to the public or EPA.

EPA officials also said that more timely access to FSIS’s test results 

would enhance their risk assessment activities. They said that FSIS is 

required to publish data within 2 years of it being collected, whereas AMS 

provided EPA with data in about 9 months after it was collected. The 

USDA Inspector General’s 2010 report on the National Residue Program 

also raised the issue of the time it took for data sharing and 

recommended that FSIS work with EPA and FDA to develop a formal 

plan with reasonable time frames to facilitate the exchange of residue 

testing data between the agencies. FSIS concurred with the 

recommendation saying that in conjunction with the other agencies it 

would include a formal plan for exchanging residue testing data in a draft 

Memorandum of Understanding (MOU) by March 2011. The draft MOU 

would revise a 1984 MOU between FSIS, AMS, EPA, and FDA that 

addresses a number of issues related to the agencies’ regulatory 

activities concerning residues of drugs, pesticides, and environmental 

contaminants in foods, including the sharing of test results. As of May 

2014, according to agency officials, the MOU for exchanging residue 

testing data had been drafted but had yet to be signed by the agencies’ 

responsible officials.

In the meantime, EPA and FSIS officials said that after discussion the 

agencies agreed that FSIS will provide EPA with specific pesticide 

residue data, on a quarterly basis, in an electronic format starting in fiscal 

year 2015. EPA determined that the agreed-upon data will contain 

enough information for its pesticide risk assessments, and FSIS 

Format and Timing of FSIS 

Data
 

Page 48 GAO-15-38 Pesticide Residue Monitoring

determined that the data are not sensitive and can be released to the 

public.

For 10 highly consumed commodities, data from the most recent year in 

which they were tested by AMS’s Pesticide Data Program show that the 

frequency with which pesticide residues were detected at any level and 

the average number of pesticides per sample varied by commodity and 

that the average levels of detected residues were well below the 

tolerance levels established by EPA.75 However, there are limitations in 

AMS’s survey methods. Specifically, while EPA officials and others have 

said that the Pesticide Data Program provides valuable information on the 

incidence and level of residues in foods, limitations in AMS’s sampling 

methods may affect the usefulness of the data in making national 

estimates about the presence of pesticide residues in the food supply, 

and AMS does not disclose these limitations, reducing transparency 

regarding the agency’s methods for collecting the data.

We analyzed pesticide residue data generated by AMS’s Pesticide Data 

Program for 10 highly consumed and frequently sampled commodities 

and found that the average number of pesticide residues per sample 

ranged widely among the 10 commodities. In some of the instances, AMS 

detected only 1 pesticide residue, and in one commodity the agency 

found as many as 17 pesticide residues in a sample. According to AMS 

officials, these findings are due to inherent differences in commodities’ 

vulnerability to pests and the resultant need to use pesticides to respond 

to varying pest pressures.

AMS’s Pesticide Data Program cooperates with state agriculture 

departments and other federal agencies to annually collect, analyze, and 

report the type and concentration of pesticide residues on agricultural 

commodities in the U.S. food supply, with an emphasis on those 

commodities highly consumed by infants and children. The program 

typically takes approximately 500 to 750 samples each for about 20 

 

75As discussed, AMS detected what it terms “presumptive tolerance violations” in some 

samples of the 10 selected commodities. Those were samples in which it found residues 

above an established tolerance or residues for which there was no established tolerance. 

AMS’s Survey Data 

Show Pesticide 

Residues Vary by 

Commodity and Are 

Generally Well below 

Tolerance Levels, but 

Annual Reports Do 

Not Disclose Survey 

Limitations

The Number of Pesticides 

per Sample Found by 

AMS’s Pesticide Data 

Program Has Varied by 

Commodity
 

Page 49 GAO-15-38 Pesticide Residue Monitoring

commodities each year.76 We selected the 10 commodities that AMS 

sampled with the most frequency from 1994 through 2012: apples, 

bananas, broccoli, cantaloupe, green beans, lettuce, peaches, pears, 

potatoes, and sweet bell peppers. We then analyzed AMS’s data for 

those commodities from the 3 most recent years in which the agency 

sampled them.77

Our analysis of AMS data shows that 9 of the commodities had residues 

in the vast majority of samples. For example, in 2008, about 96 percent of 

sampled peaches had at least one detected residue, and in 2010, about 

99 percent of sampled apples had at least one detected residue. Only 

one of the commodities, cantaloupe, had pesticide residue detections in 

less than half (about 39 percent) of AMS’s samples. Table 6 presents the 

percentage of samples with one or more detected pesticide residues in 

the most recent year of testing by AMS.

The years in which AMS tested samples are not the 

same for every commodity because AMS uses a staggered sampling 

schedule. According to AMS officials, the agency uses this schedule to 

provide current residue data for the most highly consumed commodities 

while using its resources efficiently; highly consumed commodities are 

rotated into the program every 5 years and tested for a period of 2 

consecutive years.

 

76AMS has developed Standard Operating Procedures for collecting samples. These 

procedures provide direction to state agency personnel in how to select and handle 

samples. For example, the procedures specify that the weight or volume of each sample 

must be within 20 percent of a specified amount, such as 3 pounds for small, low-weight 

commodities (e.g., mushrooms or tangerines) or 5 pounds for larger, high-weight 

commodities (e.g., cabbage or winter squash).

77We selected the commodities with the greatest number of sampling years in order to 

have a sufficient amount of data for our analysis. The earliest year we analyzed was 1998; 

the most recent year was 2012.
 

Page 50 GAO-15-38 Pesticide Residue Monitoring

Table 6: Percentage of Samples with One or More Detected Pesticide Residues in 

the Most Recent Year of Testing by the Agricultural Marketing Service’s (AMS) 

Pesticide Data Program

Commodity

Year of most

recent testing

Percentage of

samples with one or

more detected residues 

Apples 2010 99.19% 

Bananas 2012 77.28%

Broccoli 2007 88.04%

Cantaloupe 2011 38.57%

Green beans 2008 69.91%

Lettuce 2010 85.47%

Peaches 2008 95.78%

Pears 2010 74.56%

Potatoes 2009 92.34%

Sweet bell peppers 2010 87.77%

Source: GAO analysis of AMS data. | GAO-15-38

Note: All margins of error for 95 percent confidence intervals are less than plus or minus 5 

percentage points.

While the majority of AMS’s samples of these commodities had at least 

one detected residue in recent years, our analysis found that there was 

substantial variation in the average number of pesticide residues detected 

in each sample. For example, AMS’s most recent tests of these 10 

commodities detected an average of 0.55 pesticides on cantaloupe 

samples in 2011, and an average of 5.2 pesticides on apples in 2010. 

AMS’s most recent testing for the remaining 8 commodities found 

average pesticide detections within that range. Table 7 presents the 

average number of pesticides detected per sample in the most recent 

years of AMS’s sampling of the 10 commodities.
 

Page 51 GAO-15-38 Pesticide Residue Monitoring

Table 7: Average Number of Pesticides Detected per Sample in the Most Recent 

Year of Testing by the Agricultural Marketing Service’s (AMS) Pesticide Data 

Program

Commodity

Year of most

recent testing

Average

number of pesticides

detected per sample

Maximum number of

pesticides detected

in a single sample 

Apples 2010 5.20 13

Bananas 2012 1.26 4 

Broccoli 2007 1.69 6 

Cantaloupe 2011 0.55 4 

Green beans 2008 1.88 9 

Lettuce 2010 3.44 13

Peaches 2008 3.50 10

Pears 2010 1.71 8 

Potatoes 2009 1.88 8 

Sweet bell peppers 2010 4.30 17

Source: GAO analysis of AMS data. | GAO-15-38

Note: All relative margins of error for 95 percent confidence intervals are less than plus or minus 11 

percent of the numerical estimate itself.

In general, AMS’s data show that, when pesticide residues were 

detected, they were at concentrations that were well below their 

established tolerances. We analyzed AMS’s data for each of the 10 

commodities to identify the four pesticide residues with the highest 

average concentration relative to each pesticide’s tolerance.78

 

78We did not consider in this analysis those pesticides that AMS detected that did not 

have an established tolerance for that commodity. 

Among the 

most recent AMS data for the 10 commodities, potatoes generally had the 

highest average concentration of residues relative to tolerance, but those 

concentrations were still low relative to the established tolerance level. 

Specifically, the average residue concentration as a percentage of 

tolerance for the top four pesticides detected in potatoes in 2009, ranged 

from an average of 0.94 percent for the pesticide boscalid to an average 

of 9.93 percent for the pesticide azoxystrobin. The residues AMS 

detected on the other 9 commodities generally had similar or lower 

average concentrations relative to their tolerances. In broccoli, for 

example, the four pesticides with the highest average residue 

For All Selected 

Commodities, Average 

Detected Residue Levels 

Have Been Well Below 

Tolerance Levels
 

Page 52 GAO-15-38 Pesticide Residue Monitoring

concentrations averaged well below 1 percent of their tolerances in 2007. 

Table 8 presents the highest average pesticide residue concentration as 

a percentage of tolerance in the most recent year of AMS testing for all 10 

commodities. 

Table 8: Highest Average Pesticide Residue Concentration as a Percentage of 

Tolerance in the Most Recent Year of Testing by the Agricultural Marketing 

Service’s (AMS) Pesticide Data Program

Commodity

Year of most

recent testing

Pesticide with

the highest 

concentration 

relative to tolerance

Average 

concentration

of pesticide as

a percentage

of tolerance

Apples 2010 Thiabendazole 5.20%

Bananas 2012 Thiabendazole 0.66%

Broccoli 2007 Cyhalothrin 0.12%

Cantaloupe 2011 Dinotefuran 0.93%

Green beans 2008 Acephate 2.40%

Lettuce 2010 Cyhalothrin 0.60%

Peaches 2008 Fludioxonil 4.80%

Pears 2010 Pyrimethanil 2.85%

Potatoes 2009 Azoxystrobin 9.93%

Sweet bell peppers 2010 Thiamethoxam 2.80%

Source: GAO analysis of AMS data. | GAO-15-38

Note: All relative margins of error for the average concentration as a percentage of tolerance are less 

than plus or minus 40 percent of the numerical estimate itself, except for potato and broccoli, which 

are less than plus or minus 62 and 90 percent, respectively.

Because there have been improvements in the scope and precision of 

AMS’s testing program and changes in EPA’s established tolerances, 

AMS’s residue data are not directly comparable over time. Since the start 

of the Pesticide Data Program in 1991, AMS’s testing methods have 

improved in two ways that limit comparison of residue data over time. 

First, over the history of the program, the agency and its state partners 

have adopted improved testing methods that can reliably detect lower 

concentrations of residue. The ability to detect lower concentrations of 

residue has enabled AMS to reliably detect more residues in recent years 

than in earlier years. Second, with the new testing methods, AMS has 

added to the list of pesticides that are tested for each year. Additions to 

the list of pesticides that AMS tests for in a particular commodity have 

often led to additional detections. In addition, EPA has revised the 

established tolerances for particular pesticide and commodity 
 

Page 53 GAO-15-38 Pesticide Residue Monitoring

combinations. Changes in the tolerance established by EPA could affect 

calculations of residue concentration as a percentage of tolerance. For 

example, the same residue concentration found in year 1 and year 2 

would represent different percentages of the tolerance if the tolerance 

were lowered or increased in the second year. We analyzed AMS’s data 

using methods to control for these changes, and we found that doing so 

substantially affected the information regarding residue detections in each 

year. Appendix III provides further explanation of the methods we used in 

that analysis and our results.

The Pesticide Data Program provides valuable information on residues 

that stakeholders find useful, but limitations in AMS’s survey methods 

may affect the quality of program data and not disclosing these limitations 

in the program’s annual reports reduces transparency regarding the 

survey methods used, and as a result, users may not have accurate 

information and may misinterpret the program’s test results. In particular, 

AMS does not fully meet best practices in survey research, including 

some practices found in OMB standards, described above, on designing 

and releasing to the public information concerning a data collection effort. 

For example, AMS does not fully disclose in annual reports limitations in 

the Pesticide Data Program’s survey methods that could lead to biased 

results and does not present measures of total survey error (sampling 

and nonsampling)79

EPA, FDA, and nongovernment stakeholders familiar with AMS’s data 

have praised their value. Specifically, officials from EPA’s Office of 

Pesticide Programs said that the results generally provide what they need 

for conducting assessments of pesticide risks. Furthermore, FDA officials 

said that they use the data to inform their own monitoring program, such 

as by increasing attention to commodities that were shown by AMS to 

have a history of residue problems. In addition, nongovernmental 

organizations and interested parties from the pesticide industry, 

academia, and a food safety organization, said that AMS’s data are 

valuable and reliable. At the same time, EPA officials noted that AMS’s 

survey may have sampling biases that could affect its results. For 

for estimates that result from a statistical survey, 

thereby diminishing users’ ability to interpret the data.

 

79Total survey error is the difference between a population parameter (such as the mean, 

total, or proportion) and the estimate of that parameter based on the sample survey or 

census. It has two components: sampling error and nonsampling error. 

AMS’s Pesticide Data 

Program Provides 

Valuable Information but 

Does Not Disclose Survey 

Limitations
 

Page 54 GAO-15-38 Pesticide Residue Monitoring

example, officials from EPA’s Office of Pesticide Programs said that AMS 

is limited by not having a complete record of all food distribution centers 

from which to draw samples or documentation on how centers that are 

not included in its records may differ from those that are included, if at 

all.80

The survey methods used by AMS in the Pesticide Data Program meet 

many best practices for meeting OMB’s standards on designing and 

releasing to the public information concerning a data collection effort but 

do not meet several others, particularly those that are designed to ensure 

that the sample design will yield survey data that can form the basis of 

statistically valid estimates to represent a population of interest, in this 

case about the extent of pesticide residues in the U.S. food supply. 

AMS’s surveys are based on some principles of statistically valid sample 

design—including random selection of distribution centers for which it has 

records within selected states that were invited and agreed to participate 

and commodities within those centers—and the laboratory tests of those 

commodities are based on scientifically established protocols for handling 

commodity samples and measuring pesticide concentrations. These are 

important quality assurance steps that are meant to select an unbiased 

sample of commodities in the food supply and to produce accurate 

residue detections on sampled items.

Officials from AMS noted that the agency relies on the participating 

states to seek cooperation from distribution centers. Officials from AMS 

also noted that the agency does not have the authority to require that 

distribution centers participate in the survey, as participation in the 

program is voluntary. In addition, they noted that no site selected from the 

list of volunteer centers has ever refused to participate.

In addition, the program does not meet other best practices including 

those designed to provide the public with access to useful information. 

For example, AMS does not demonstrate the extent to which the 

commodities that it selects to sample (e.g., apples or pears) represent all 

commodities in the food supply or demonstrate the extent to which the 

distribution centers that participate represent all distribution centers in the 

country—an important limitation because the majority of states do not 

 

80Sampling bias in this case implies that the food distribution centers under consideration 

are not representative of all food distribution centers.
 

Page 55 GAO-15-38 Pesticide Residue Monitoring

participate in the program.81 AMS also does not disclose whether, to 

accurately represent the U.S. food supply, samples selected from some 

distribution centers should be weighted differently than other samples 

because they were more or less likely to be selected or to correct for 

differences between the sample and the U.S. food supply. If pesticide 

residue concentrations on excluded commodities are significantly different 

from those on selected commodities or concentrations on commodities 

from participating distribution centers are significantly different from those 

in nonparticipating distribution centers, the Pesticide Data Program data 

may not accurately represent pesticide concentrations in the U.S. food 

supply. Without this information, users of the data may misinterpret 

AMS’s annual monitoring reports and draw erroneous conclusions based 

on the data.

FDA and FSIS face a formidable task in monitoring and enforcing 

pesticide residue tolerances associated with thousands of pesticide and 

commodity combinations that play a critical role in food production by 

helping to minimize crop losses due to pests and weeds. As part of this 

task, FDA and FSIS are to determine that pesticide residues in food do 

not exceed established tolerances in order to ensure food safety and 

protect human health.

While there is no requirement that FDA or FSIS test for all the pesticides 

for which EPA has established a tolerance, OMB directs agencies to meet 

certain standards when designing and releasing information to the public 

concerning a data collection effort. FDA tests for the majority of pesticides 

that have established tolerances, but the agency does not disclose the 

pesticides with tolerances for which it does not test or the potential effect 

that not testing could have on its detection of violations. Such a disclosure 

would be consistent with OMB best practices for reporting limitations 

relevant to analyzing and interpreting results from a data collection effort. 

Our review found that FDA does not test for several commonly used 

pesticides, including glyphosate, or disclose the potential effects of not 

testing for these pesticides. In addition, while FSIS has recently increased 

the scope of its testing, the agency does not disclose that it does not test 

for specific pesticides that have tolerances for animal products or their 

 

81AMS could not provide a quantitative assessment of the extent to which all distribution 

centers within participating states were invited to participate in the Pesticide Data 

Program. 

Conclusions
 

Page 56 GAO-15-38 Pesticide Residue Monitoring

feed or the potential effect of not testing for these pesticides. By not 

disclosing in their annual monitoring reports the pesticides that have 

tolerances for which they do not test and the potential effects of not 

testing for them, consistent with OMB best practices, users of the 

agencies’ annual reports may not have accurate information and may 

misinterpret the results of the programs.

In addition, FDA’s monitoring program focuses on testing commodities 

that have been targeted as part of monitoring for compliance and 

enforcement to the exclusion of determining the incidence and level of 

pesticide residues in imported and domestic foods—one of FDA’s stated 

objectives. OMB standards direct agencies to use generally accepted 

statistical methods for collecting and reporting data. In this context, a 

generally accepted statistical method to obtain a valid estimate that 

represents a population would include either (1) testing a statistically valid 

sample of that population or (2) justifying statistically a nonprobability 

method that can measure the estimation error. According to FDA officials, 

calculating national estimates of pesticide violations for the entire food 

supply it regulates would be very expensive. However, FDA’s focus on 

targeted samples limits the agency’s ability to make valid national 

estimates about violation rates for imported and domestic foods since the 

targeted samples it collects cannot be the basis of statistically valid 

national estimates. Therefore, the annual pesticide monitoring reports do 

not reliably reflect the rate at which pesticide violations occur in the U.S. 

food supply, limiting their usefulness as a potential source of national 

estimates. Further, without reliable nationally representative data with 

which to evaluate how effective its targeted monitoring program is in 

identifying and intercepting violative foods, FDA cannot compare the rate 

of violations detected through the program with the overall rate of 

pesticide residue violations within the imported and domestic food 

supplies. Therefore, this limitation of testing only targeted commodities 

affects FDA’s ability to evaluate the effectiveness of its PREDICT 

targeting tool and, ultimately, FDA’s ability to reliably identify specific 

commodities that may be at high risk of violating pesticide residue 

tolerances is limited.

Finally, the sampling methodology used by AMS in the Pesticide Data 

Program meets many of the best practices for meeting OMB’s standards 

on designing and releasing to the public information concerning a data 

collection effort, but it does not meet several others. For example, AMS 

does not disclose in the program’s annual reports the potential effect of 

any bias associated with participating states or food distribution centers, 

or its selection of commodities, and does not report or direct data users 
 

Page 57 GAO-15-38 Pesticide Residue Monitoring

on how to obtain appropriate sampling error (margins of error) for 

estimates that result from a statistical survey, as called for by OMB’s 

statistical survey standards. By not disclosing these potential sources of 

survey error, the agency’s monitoring reports do not meet OMB best 

practices because they do not include all information necessary for users 

to analyze the data properly or to assess the quality of results, which may 

lead users to misinterpret AMS’s annual monitoring reports and draw 

erroneous conclusions based on the survey data.

We are making five recommendations to the Secretary of Health and 

Human Services and four recommendations to the Secretary of 

Agriculture.

To better inform users of the annual monitoring report about the 

frequency and scope of pesticide tolerance violations, we recommend 

that the Secretary of Health and Human Services direct the 

Commissioner of FDA to disclose in the agency’s annual pesticide 

monitoring program report which pesticides with EPA-established 

tolerances the agency did not test for in its pesticide monitoring program 

and the potential effect of not testing for those pesticides.

To gather and report reliable, nationally representative data on pesticide 

residue violations, we recommend that the Secretary of Health and 

Human Services direct the Commissioner of FDA to

• design and implement a statistically valid sampling methodology that 

would enable the agency, within existing resources, to gather 

nationally representative pesticide residue incidence and level data for 

both domestically produced and imported foods, or justify statistically 

the use of a nonprobability method that can measure the estimation 

error. In designing either approach, FDA should consider the extent to 

which the benefits exceed the costs; and

• report the nationally representative incidence and level data in its 

annual pesticide monitoring reports, including disclosing the limits of 

its chosen sampling methodology.

To evaluate and refine its targeted pesticide compliance and enforcement 

monitoring program, we recommend that the Secretary of Health and 

Human Services direct the Commissioner of FDA to use the incidence 

and level data to

Recommendations for 

Executive Action
 

Page 58 GAO-15-38 Pesticide Residue Monitoring

• assess the effectiveness of FDA’s targeted pesticide compliance and 

enforcement monitoring program, including its use of the PREDICT 

targeting tool for imported foods, by comparing the rate of violations 

detected through the program to the overall rate of pesticide residue 

violations within the domestic and imported food supplies; and

• identify any types of domestic and imported foods that are at high risk 

for pesticide residue tolerance violations to improve the ability of its 

targeted pesticide compliance and enforcement monitoring program to 

consistently identify food likely to have violations.

To better inform the public about the frequency and scope of pesticide 

tolerance violations, we recommend that the Secretary of Agriculture 

direct the FSIS Administrator to disclose in the agency’s annual pesticide 

monitoring program report which pesticides with EPA-established 

tolerances the agency did not test for in its National Residue Program and 

the potential effect of not testing for those pesticides.

To better meet federal standards and best practices for statistical 

surveys, we recommend that the Secretary of Agriculture direct the AMS 

Administrator to provide better documentation of the survey methods 

used in its Pesticide Data Program in the program’s annual reports by

• providing more complete information on the sampling methodology 

the agency uses, such as how it identifies and selects states, food 

distribution centers, and commodities for pesticide residue testing, 

and include measures of sampling error for reported estimates,

• reporting on the extent to which its survey covers commodities in the 

U.S. food supply and any limitations associated with its survey 

methodology; and

• describing methods users should employ to analyze the data, 

including obtaining margins of error for making generalizeable 

estimates of pesticide residues in commodities.

We provided a draft of this report to the Department of Health and Human 

Services (HHS) on behalf of FDA, USDA, and EPA for review and 

comment. HHS and USDA provided written comments on the draft, which 

are presented in appendixes IV and V, respectively. Of the five 

recommendations that were directed to it, HHS agreed with two, neither 

agreed nor disagreed with two, and disagreed with one. In its written 

comments, USDA stated it generally agreed with the four 

recommendations that were directed to it and described actions it planned 

to take to address them. In an e-mail received on August 25, 2014, an 

Agency Comments 

and Our Evaluation
 

Page 59 GAO-15-38 Pesticide Residue Monitoring

official from EPA’s GAO Liaison Team stated that EPA had no comments 

on our report.

In its written comments, HHS said that it has already increased its 

monitoring of pesticide residues by taking actions consistent with our 

recommendations and discussed ways in which the agency has 

increased the scope of its testing program. In addition, HHS noted that 

FDA’s food safety mission also includes protecting consumers against 

foodborne illnesses due to microbiological contamination and that the risk 

of microbiological contamination, rather than pesticide contamination, 

often drives the agency’s decisions about using its limited resources. We 

appreciate FDA’s efforts to increase the scope of its pesticide residue 

program and understand that it faces a difficult task in protecting 

consumers from many types of food contamination. 

HHS disagreed with our first recommendation that FDA disclose in its 

annual pesticide monitoring program report which pesticides with EPAestablished tolerances FDA did not test for and the potential effect of not 

testing for those pesticides. HHS said that future versions of FDA’s 

annual report will clarify that not all pesticides with EPA-established 

tolerances were analyzed. However, HHS disagreed with naming the 

pesticides that were not assessed and said that FDA’s annual report is 

intended to comply with requirements of the Pesticide Monitoring 

Improvements Act of 1988. HHS stated that in its annual report, FDA 

discloses all pesticides tested for within the report’s annual scope, as 

required by the act, including many pesticides that do not have EPAestablished tolerances. In addition, HHS said that it believes that 

disclosing pesticides for which FDA does not test would enable users to 

more easily circumvent the pesticide monitoring program. 

We believe that OMB’s guidelines for releasing information to the public 

concerning a data collection effort are also applicable to FDA’s pesticide 

monitoring program, and based our recommendation on those 

guidelines.82

 

82OMB, Standards and Guidelines for Statistical Surveys (September 2006). 

 OMB directs agencies to produce survey documentation 

that includes those materials necessary to understand how to properly 

analyze data from each survey. In our view, disclosing the pesticides that 

are not included in FDA’s testing program would be consistent with OMB 

best practices for reporting limitations relevant to analyzing and 
 

Page 60 GAO-15-38 Pesticide Residue Monitoring

interpreting results from a data collection effort. With regard to HHS’s 

comment that pesticide users might more easily circumvent the 

monitoring program if they knew which pesticides FDA did not test for, we 

note that a user seeking to circumvent the pesticide monitoring program 

could do so now by reviewing the list of pesticides FDA tested for that it 

publishes in its annual reports. We also note that HHS did not comment 

on whether or how FDA’s future annual program reports would disclose 

the potential effects of not testing for certain pesticides that have EPAestablished tolerances. We continue to believe that it is important for 

users of the annual reports to know the extent to which certain pesticides 

are excluded from testing and that the agency may be identifying fewer 

pesticide residue violations than are occurring. Thus, we continue to 

believe that FDA should fully implement the recommendation. 

In its written comments, HHS said that FDA would investigate the 

feasibility and potential costs of implementing our second 

recommendation that the agency design and implement a statistically 

valid sampling methodology for its pesticide monitoring program. 

According to HHS, implementing a program for systematic statistical 

sampling would require additional resources or, given existing resources, 

a reduction in the variety of commodities that FDA would analyze 

annually. HHS added that AMS’s Pesticide Data Program generates 

national statistically valid data that FDA uses to inform the risk value in 

PREDICT and which commodities to target for testing. 

We welcome FDA’s decision to investigate the feasibility of enhancing its 

monitoring program. Implementing a statistically valid sampling 

methodology would be necessary to attain the agency’s objective to 

determine the incidence and level of pesticide residues in domestic and 

imported foods.83

 

83FDA, Compliance Program Guidance Manual: Chapter 04—Pesticide and Chemical 

Contaminants, 7304.004 (June 27, 2011). 

 In our view, nationally representative data collected by 

FDA would provide a more accurate picture of the pesticide residue 

violation rate throughout the food supply and would also enable the 

agency to evaluate the monitoring program’s effectiveness and refine its 

targeting efforts under PREDICT, topics addressed in our fourth and fifth 

recommendations. While we recognize the value provided by AMS’s 

Pesticide Data Program, we note that the data generated by AMS were 

not intended to be used for the purpose of evaluating the effectiveness of 
 

Page 61 GAO-15-38 Pesticide Residue Monitoring

FDA’s program. As we state in the report, AMS’s Pesticide Data Program 

tests large sample sizes but takes samples from relatively few 

commodities each year and thus cannot be used to directly and reliably 

evaluate the effectiveness of FDA’s monitoring program across the 

domestic and imported food supplies. 

HHS did not commit to implementing our third recommendation that FDA 

report nationally representative incidence and level data in its annual 

reports, but did agree that FDA would disclose the limitations associated 

with its monitoring program in its annual reports. In its written comments, 

HHS explains that the FDA pesticide program is targeted in nature. As we 

state in the report, determining the incidence and level of pesticide 

residues in imported and domestic foods is one of FDA’s stated 

objectives. However, FDA’s focus on targeted samples limits the agency’s 

ability to make valid national estimates about violation rates for imported 

and domestic foods since the targeted samples it collects cannot be the 

basis of statistically valid national estimates. Thus, we continue to believe 

that FDA should fully implement this recommendation.

HHS concurred with our fourth recommendation that FDA assess the 

effectiveness of its targeted pesticide compliance and enforcement 

monitoring program, including its use of PREDICT. HHS described FDA’s 

ongoing effort to evaluate (1) the effectiveness of regulatory actions in 

preventing future violative shipments by reviewing incidences of repeat 

violations among growers, shippers, importers, consignees, dealers, 

filers, and harvesters over the past 3 years and (2) risks associated with 

PREDICT. While we welcome FDA’s efforts to evaluate its program, we 

continue to believe that a comprehensive evaluation cannot be 

successfully completed without statistically valid data on the national 

incidence and level of pesticide residues.

Similarly, HHS generally concurred with our fifth recommendation that 

FDA identify any domestic and imported foods that are at high risk for 

pesticide residue tolerance violations to improve the ability of its targeted 

pesticide compliance and enforcement monitoring program to consistently 

identify foods likely to have violations. In its written comments, HHS said 

that FDA actively identifies and targets commodities that are at high risk 

for pesticide residue violations. We do not believe that FDA can be sure 

that it is targeting high risk commodities without statistically valid data on 

the incidence and level of violations in commodities. 

In its written comments, USDA stated that it generally agreed with our 

findings and our four recommendations directed to the agency but wanted 
 

Page 62 GAO-15-38 Pesticide Residue Monitoring

to emphasize some of the differences in its agencies’ missions with 

respect to monitoring pesticide residues. In response to our four 

recommendations, USDA said that

• FSIS will disclose in its annual pesticide monitoring program 

reports which pesticides with an EPA-established tolerance the 

agency did not test for in the National Residue Program and the 

potential effect of not testing for those pesticides. USDA also said 

that FSIS will continue to insert or remove pesticides from its 

testing program based on their public health importance and will 

continue discussions with EPA on the minimum level of 

applicability (i.e., the lowest valid residue concentration reported 

by a test method) for those pesticides tested by FSIS or those 

prioritized for testing by EPA;

• AMS plans to add a description of the sampling methodology 

employed for selecting states, food distribution centers, and 

commodities for inclusion in the Pesticide Data Program annual 

summary report and explore procedures for assessing the degree 

to which incompleteness in the sampling frame may lead to the 

potential for biased estimates;

• AMS plans to provide more information on its sampling 

methodology, program parameters, and inherent limitations in its 

methodology in the Pesticide Data Program annual summary 

report. AMS believes that the participating sites provide a reliable 

representation of all sites and will investigate methods for 

confirmation; and

• AMS will work to describe methods users can use to analyze 

Pesticide Data Program data and to improve the sampling 

methodology. Once developed, such methods and procedures will 

be included in the Pesticide Data Program annual summary 

report. USDA did not mention whether it would describe methods 

for users of the data to obtain margins of error, which we believe 

is important to help users analyze the data.

FDA also provided us with technical comments, which we incorporated as

appropriate.

As agreed with your office, unless you publicly announce the contents of 

this report earlier, we plan no further distribution until 30 days from the 

report date. At that time, we will send copies to the appropriate 
 

Page 63 GAO-15-38 Pesticide Residue Monitoring

congressional committees, the Secretary of Agriculture, the Secretary of 

Health and Human Services, the Commissioner of FDA, the Administrator 

of EPA, and other interested parties. In addition, the report will be

available at no charge on the GAO website at http://www.gao.gov. 

If you or your staff members have any questions about this report, please 

contact me at (202) 512-3841 or neumannj@gao.gov. Contact points for 

our Offices of Congressional Relations and Public Affairs may be found 

on the last page of this report. GAO staff who made key contributions to 

this report are listed in appendix VI.

Sincerely yours,

John Neumann

Acting Director, Natural Resources and Environment
Appendix I: Objectives, Scope, and 

Methodology

Page 64 GAO-15-38 Pesticide Residue Monitoring

This report examines (1) what the Food and Drug Administration (FDA) 

data show with respect to pesticide residue violations in the foods that it 

regulates and limitations, if any, in its efforts to monitor foods for pesticide 

violations; (2) what the Food Safety and Inspection Service (FSIS) data 

show with respect to pesticide residue violations in the foods that it 

regulates and limitations, if any, in its efforts to monitor foods for pesticide 

violations; and (3) what the Agricultural Marketing Service (AMS) data 

show with respect to pesticide residue levels in fruits, vegetables, and 

other foods, and limitations, if any, in its efforts to gather and report that 

information.

To examine what is known about pesticide residue in food and violations 

of residue tolerances, we analyzed data from the FDA, the U.S. 

Department of Agriculture’s (USDA) FSIS, and USDA’s AMS. We 

evaluated the reliability of these data by reviewing or discussing the 

agencies’ management controls to ensure the data’s accuracy and 

completeness. As appropriate, we also reviewed the agencies’ 

compliance with the Office of Management and Budget’s (OMB) 

Standards and Guidelines for Statistical Surveys.

1

FSIS is responsible for examining and inspecting meat, poultry, and 

processed egg products to ensure their safety. FDA is responsible for 

regulating to ensure the safety of virtually all other foods. AMS collects 

residue data on a wide range of foods for informational purposes. Much of 

our analyses of FDA’s and AMS’s residue test results focused on 10 

selected fruit and vegetable commodities that are highly consumed in the 

United States.

We found these data to 

be sufficiently reliable for purposes of making estimates of the extent of 

pesticide residues and residue violations in food, although where 

discussed we note limitations in the methods the agencies have used to 

collect these data. 

2

Our analysis of FDA’s data for those commodities covered 1993 through 

2012, and our analysis of AMS’s data for the commodities collectively 

We selected these 10 commodities because they were 

the commodities AMS tested for most often from 1994 through 2012 and 

for which the agencies had data sufficient for our purposes.

 

1

OMB, Standards and Guidelines for Statistical Surveys (September 2006). 

2

These 10 commodities were apples, bananas, broccoli, cantaloupe, green beans, lettuce, 

peaches, pears, potatoes, and sweet bell peppers.

Appendix I: Objectives, Scope, and 

Methodology
Appendix I: Objectives, Scope, and 

Methodology

Page 65 GAO-15-38 Pesticide Residue Monitoring

spanned 1998 through 2012. We also analyzed FSIS’s monitoring data 

from 2000 through 2011 to report information about pesticide residues 

found in meat, poultry, and egg products. For each agency, the data we 

analyzed were the most recent available at the time of our review. In 

addition, our analysis included a review of certain aspects of FDA’s 

domestic and imported food inspection process, FSIS’s National Residue 

Program, and the methodology AMS has used to gather residue data 

through its Pesticide Data Program.

Our review of FDA’s pesticide residue monitoring program included an 

analysis of the agency’s monitoring results, which are discussed in more 

detail in appendix II, as well as a review of its monitoring approach.

To examine pesticide residue violations in the foods that it regulates, we 

analyzed FDA’s pesticide residue monitoring data from the years for 

which it had electronic data—1993 through 2012, excluding 2004.3 FDA 

provided us with electronic files for those years containing pesticide 

residue data for all food commodities that it tested, but we focused our 

analysis on 10 commodities—apples, bananas, broccoli, cantaloupe, 

green beans, lettuce, peaches, pears, potatoes, and sweet bell peppers. 

We selected 10 commodities that AMS identified as being widely 

consumed in the U.S. diet and for which FDA and AMS had testing data 

during that time period. More specifically, we selected the 10 because 

they were the commodities that AMS had tested most often during the 

history of the Pesticide Data Program. The AMS program has tested over 

90 commodities for pesticide residues, with an emphasis on commodities 

that are highly consumed by infants and children.4 Typically, AMS tests 

commodities for a range of different pesticides about every 5 years for 2 

years in a row.5

 

3

FDA was not able to provide us with test results from 2004 that were comparable in detail 

to the other years. Therefore, we could not include that year in our analysis of pesticide 

residue test results. 

AMS tested the 10 selected commodities in at least 8 

years from the beginning of the program in 1991 through 2012. We used 

the same group of 10 commodities for our analysis of FDA and AMS data 

4

In addition to raw commodities, AMS also tests processed commodities such as canned 

vegetables, frozen fruit, fruit juices, and baby foods. 

5

In some instances, AMS tested commodities for a specific subset of pesticides. For 

example, in 1999, AMS conducted two separate special pesticide residue tests for classes 

of pesticides known as organophosphates and carbamates in apples. 

FDA’s Pesticide Residue 

Monitoring Program

Analysis of FDA Data for 

Types and Origin of Pesticide 

Residue Violations
Appendix I: Objectives, Scope, and 

Methodology

Page 66 GAO-15-38 Pesticide Residue Monitoring

on pesticide residue violations to enable consistent presentations of the 

two agencies’ results.

We analyzed the FDA data using Statistical Analysis System software to 

determine the types and origins of violations that the agency detected for 

each of the 10 commodities. There are two types of pesticide residue 

violations. In the first instance, FDA detects a pesticide residue in an 

amount that exceeds the tolerance that the Environmental Protection 

Agency (EPA) has established. That is known as a violation of tolerance. 

In the second instance, FDA detects the residue of a pesticide for which 

EPA has not established a tolerance for that particular commodity. That is 

known as a violation of no tolerance. In some cases, FDA may detect the 

residue of a pesticide that is no longer registered for any use in the United 

States but for which FDA (in consultation with EPA) has established a 

maximum residue level, or “action level,” to account for the fact that the 

pesticide may persist in the environment for long periods of time after its 

use is discontinued.6

Because FDA data on violations were derived from a sampling method 

designed, at least in part, to target foods with a high risk of violation, 

rather than from a statistically generalizable sample, FDA rates are not 

intended to be interpreted as reliable estimates of the actual violation 

rates among these 10 commodities in the food supply. Therefore, to 

determine violation rates for these commodities, we also analyzed AMS 

data that indicate the presence of residues that exceed tolerances and 

If FDA detects residue that exceeds an action level, 

it considers, on a case-by-case basis, whether to take an enforcement 

action to remove the food from the market. We also identified whether the 

samples that FDA tested were from the United States (domestic) or 

imported from another country. Finally, we reviewed FDA annual reports 

from 2008 through 2012 to gather data on pesticide residue violations the 

agency detected in all foods that it sampled, including the origin of the 

foods FDA found to have residue violations.

 

6

An action level specifies the level below which FDA exercises its discretion not to take 

enforcement action. 
Appendix I: Objectives, Scope, and 

Methodology

Page 67 GAO-15-38 Pesticide Residue Monitoring

present these results with the limitations discussed in the report.7

To examine limitations, if any, in FDA’s efforts to monitor for pesticide

residue violations, we reviewed FDA documents including FDA’s annual 

pesticide monitoring reports, district work plans for sampling domestic 

commodities, guidance for sampling both domestic and imported 

commodities, and documentation related to the agency’s import scoring 

system known as Predictive Risk-based Evaluation for Dynamic Import 

Compliance Targeting (PREDICT). We interviewed agency officials from 

FDA’s Center for Food Safety and Applied Nutrition and officials from 

FDA’s Office of Regulatory Affairs who are responsible for developing 

strategies and policies for reducing health threats from contaminated 

food, monitoring foods for residue, and enforcing pesticide tolerances. 

These interviews included discussions about FDA violation data and the 

use of FDA’s import review system PREDICT, including the agency’s 

ongoing internal evaluation of that system. We visited FDA’s Baltimore 

District Office to interview officials about how agency personnel monitor 

domestic and imported foods, as well as their use of PREDICT to target 

imported foods for testing because, among other things, it receives a 

large quantity of imported foods. We also analyzed the violation rates for 

imported foods relative to their PREDICT scores in 2012, the first full year 

in which FDA used the system nationwide, to determine the relationship 

Specifically, we used Statistical Analysis System survey procedures to 

analyze AMS Pesticide Data Program data from 1998 through 2012 for 

the same commodities—where those data were available—to identify the 

rate at which AMS found residues that exceeded established tolerances 

or for which there were no tolerances. AMS refers to these situations as 

“presumptive tolerance violations.” For this analysis, we used data from 

the 3 most recent years—from 1998 through 2012—in which AMS tested 

the 10 commodities. AMS tests particular commodities on a staggered 

schedule; the earliest year of data for one of the commodities was 1998. 

We were not able to reliably compare the rate at which AMS found 

violations in most domestically grown and imported commodities because 

of small or imbalanced sample sizes.

 

7

We calculated margins of error for 95 percent confidence intervals for the AMS data and 

present them along with the estimates. However, as we described in this report, there are 

limitations in AMS’s survey methods that lead us to have some concerns about using its 

data to make national estimates about the incidence and level of pesticide residues. 

Consequently, the results of our analyses are restricted to the samples taken by AMS for 

the 10 commodities we reviewed and are not meant to be generalized to the population of 

these commodities in the food supply.

Review of FDA’s Methods for 

Monitoring Pesticide Residue 

Violations
Appendix I: Objectives, Scope, and 

Methodology

Page 68 GAO-15-38 Pesticide Residue Monitoring

between PREDICT scores and violations. In addition, we reviewed FDA’s 

sampling methods and its reporting of sampling results relative to the 

direction and guidance contained in the OMB’s Standards and Guidelines 

for Statistical Surveys and the Standards for Internal Control in the 

Federal Government, as well as other best practices in survey 

methodology.8

Our review of FSIS’s pesticide residue monitoring program included an 

analysis of the agency’s monitoring results as well as a review of its 

monitoring approach.

To examine what FSIS has found with respect to pesticide residue 

violations in meat, poultry and processed egg products, we analyzed

FSIS’s monitoring data from 2000 through 2011 to identify the types and 

frequency of pesticide residues found in those commodities. Specifically, 

we analyzed pesticide residue test results from 2000 through 2011 

published by the agency in its annual National Residue Program reports. 

Using data from FSIS’s annual reports, we identified the number of 

samples that FSIS tested for residues each year, the number of pesticide 

residue violations it detected, the types of animal products—known as 

production classes—with violations, and the types of pesticides found. 

We also analyzed the annual reports to gather data on the frequency with 

which FSIS detected pesticide residues at levels below established 

tolerances.

We analyzed the size and scope of the National Residue Program by 

reviewing FSIS’s annual sampling plans from 2010 through 2013. 

Specifically, we gathered data from the annual plans on the number of 

samples FSIS planned to take of domestic and imported products and the 

production classes that it planned to sample. With respect to the scope of 

the program, we reviewed the sampling plans and agency guidance 

documents to identify which pesticides FSIS’s testing methods were 

capable of detecting. The pesticides in FSIS’s testing program included 

some for which EPA has established tolerances for animal products and 

 

8

OMB, Standards and Guidelines for Statistical Surveys (September 2006) and 

GAO/AIMD-00-21.3.1; American Association for Public Opinion Research, Best Practices 

for Survey Research, http://www.aapor.org//Best_Practices1.htm; and Federal Committee 

on Statistical Methodology, Measuring and Reporting Sources of Error in Surveys (July

2001). 

FSIS’s Pesticide Residue 

Monitoring Program

Analysis of FSIS Data on 

Pesticide Residues in Meat, 

Poultry, and Processed Egg 

Products

Review of FSIS’s Methods for 

Monitoring Pesticide Residue 

Violations
Appendix I: Objectives, Scope, and 

Methodology

Page 69 GAO-15-38 Pesticide Residue Monitoring

others for which EPA has not established tolerances. Using information 

from EPA, we identified 18 pesticides that EPA has registered for direct 

use on animals. Using FSIS’s guidance documents, we identified which of 

the 18 pesticides registered for direct use on animals can be, or is 

planned to be, detectable by FSIS’s testing methods. We also reviewed 

FSIS’s sampling methods and the agency’s reporting of sampling results 

relative to the direction and guidance contained in OMB’s Standards and 

Guidelines for Statistical Surveys, as well as other best practices in 

survey methodology.9

We also interviewed officials at EPA’s Office of Pesticide Programs about 

EPA’s use of FSIS data in conducting risk assessments of specific 

pesticides. In particular, we discussed the EPA officials’ views on the 

adequacy of the FSIS data for EPA’s risk assessment needs. We also 

discussed with these officials EPA’s negotiations with FSIS on expanding 

the scope of the National Residue Program to test for more pesticides 

and to be able to detect lower concentrations of pesticides in beef, pork, 

and poultry. EPA officials provided us with a list of pesticides the agency 

had prioritized for FSIS to include in the National Residue Program. We 

compared EPA’s priorities with FSIS’s testing plans for 2014.

We also reviewed a 2010 report by USDA’s Office of Inspector General 

on FSIS’s residue program.10 The report contains findings, conclusions, 

and recommendations that concerned, among other things, the scope of 

FSIS’s residue monitoring. We interviewed FSIS officials to discuss the 

agency’s response to recommendations in the Inspector General’s report 

concerning the scope of the National Residue Program’s testing methods.

Our review of AMS’s pesticide residue monitoring program included an 

analysis of the agency’s monitoring results, as well as a review of its 

monitoring approach.

 

9

OMB, Standards and Guidelines for Statistical Surveys (September 2006) and 

GAO/AIMD-00-21.3.1; American Association for Public Opinion Research, Best Practices 

for Survey Research, http://www.aapor.org//Best_Practices1.htm; and Federal Committee 

on Statistical Methodology, Measuring and Reporting Sources of Error in Surveys (July

2001). 

10FSIS National Residue Program for Cattle, USDA Office of Inspector General, Audit 

Report 24601-08-KC (Mar. 25, 2010).

AMS’s Pesticide Data 

Program
Appendix I: Objectives, Scope, and 

Methodology

Page 70 GAO-15-38 Pesticide Residue Monitoring

To examine what AMS has found with respect to pesticide residue levels, 

we analyzed residue data for the 10 selected fruit and vegetable 

commodities collected by the agency’s Pesticide Data Program from 1998 

through 2012. We evaluated AMS’s sampling11 and nonsampling12 error 

according to best practices in survey research, including OMB’ s 

Standards and Guidelines for Statistical Surveys as well as other best 

practices in survey methodology.13 Using the AMS data for each of the 10 

commodities, we estimated: (1) the number of unique detections of 

pesticide residue above the limit of detection on each sample; 14 (2) the 

average number of pesticide residues per sample; (3) the four residues 

with the highest average residue concentration relative to that 

commodity’s pesticide tolerance; and (4) the number of presumptive 

tolerance violations.15

We conducted our analyses to characterize pesticide residue for the 10 

commodities using the same data in two different ways. The first analysis 

Because the AMS data were collected through 

random samples, our estimates have sampling error. Although we found 

limitations with the AMS sampling methodology, as described in the 

report, in order to produce an estimate of the sampling error, we used 

survey procedures in Statistical Analysis System software to calculate 

confidence intervals associated with each of the estimates under 

assumptions about the sampling and nonsampling error. We calculated 

these estimates under the assumption that AMS data were taken from an 

equally weighted random sample, stratified by the state in which the 

distribution center is located. We provide the details of those sampling 

errors and confidence intervals where appropriate.

 

11Sampling errors are errors associated with survey estimates that are due to sampling 

some and not all of the units in the sampling frame.

12Nonsampling errors are errors in sample estimates that do not stem from sampling, such 

as coverage error, measurement error, or data processing error. 

13OMB, Standards and Guidelines for Statistical Surveys (September 2006); American 

Association for Public Opinion Research, Best Practices for Survey Research, 

http://www.aapor.org//Best_Practices1.htm; and Federal Committee on Statistical 

Methodology, Measuring and Reporting Sources of Error in Surveys (July 2001).

14The limit of detection is the concentration of a residue that AMS could detect with 

accuracy. 

15AMS gathers its Pesticide Data Program data in an effort to estimate residue levels in 

the food supply rather than for regulatory purposes, but information about findings of 

residues that exceed pesticide tolerances or for which there is no tolerance is available to 

FDA, FSIS, and EPA. AMS calls these findings “presumptive tolerance violations.” 

Analysis of AMS Data on the 

Type and Number of Residues 

in 10 Selected Commodities
Appendix I: Objectives, Scope, and

Methodology

Page 71 GAO-15-38 Pesticide Residue Monitoring

focused on the most recent AMS data available for each commodity. We 

presented the results of that analysis in the body of this report. The 

second analysis examined AMS data at different points in time. To 

accomplish this analysis, we took steps to control for variations in how 

AMS collected the data over time, as well as changes in EPA tolerances 

so that we could reliably compare data from one year to another. We refer 

to these data as restricted data. We briefly describe the reasons for those 

restrictions and our methods below and present the results of that 

analysis in appendix III.

Analysis of Restricted AMS Data at Different Points in Time

To provide additional information on what was detected in other recent 

points in time, we examined two additional periods for each of our 10 

commodities. We identified the 3 most recent years of AMS data for our 

analysis of pesticide residue. Because AMS did not test each commodity 

each year, the 3 most recent years of data varied for each commodity. 

For example, the 3 most recent years of testing on apples were 2001, 

2004, and 2010, and the 3 most recent years for bananas were 2002, 

2006, and 2012.

To reliably compare the AMS data at different points in time, we 

accounted for changes in AMS’s testing methods and EPA’s established 

tolerances. In particular, comparing residues detected at different time 

points is complicated by the fact that the pesticides AMS tested for, the 

technology it used to detect residues, and the tolerances established by 

EPA for pesticides may change for particular commodity-pesticide 

combinations. To account for those changes, we developed methods for 

restricting the data so it could be compared at different time points for a

limited set of pesticides, higher limits of detection, and a fixed set of 

tolerance levels.

More specifically, the first change to account for was that the number of 

pesticides for which AMS’s Pesticide Data Program tested for increased 

over time as its methods became more sophisticated. The residue of a 

particular pesticide might have been present on samples of a commodity 

in each year we analyzed but could only be detected in the second or 

third year when more comprehensive testing methods included that 

pesticide. To account for increases in detections caused by an expansion 

in the number of pesticides AMS tested for, we included in our analysis 

only those pesticides AMS tested for in all 3 years. For example, AMS 

tested apples for 93, 175, and 184 pesticides in 2001, 2004, and 2010, 

respectively. The restricted list we used for our analysis consisted of the 
Appendix I: Objectives, Scope, and 

Methodology

Page 72 GAO-15-38 Pesticide Residue Monitoring

83 pesticides that AMS tested apples for in each of these years and, 

therefore, excluded 10 from 2001, 92 from 2004, and 101 from 2010. By 

focusing on a common set of pesticides, our restricted analysis, while 

standardized across the years, does not include any changes that may 

have occurred in the pesticides that were not tested.

The second change to account for was that, as the technical capabilities 

of laboratories that test for pesticide residue have improved, AMS has 

been able to reliably detect increasingly lower concentrations of residue. 

As a result, a particular pesticide residue may have been present at low 

levels in all 3 years, but was only detectable in the most recent year 

because of improved technology. AMS’s database includes the limit of 

detection for each pesticide, thereby indicating the concentration it can 

reliably detect. To account for increases in the ability to detect residues in 

later years, we used AMS’s limit of detection for each pesticide to restrict 

the data. For our analysis of different points in time, we selected the 

highest limit of detection for each commodity-pesticide combination in the 

first year and applied this to our analysis of that commodity pesticide 

combination in the remaining 2 years. By focusing on this common set of 

limits of detection, our restricted analysis, while standardized across the 

years, does not include any changes that may have occurred in the limits 

of detection for particular pesticides.

The third change to account for was that EPA’s established tolerance for 

a particular pesticide/commodity combination can change over time. 

Therefore, the concentration of pesticide residue as a percentage of 

tolerance could have changed because EPA changed the tolerance 

rather than because the concentration changed. To account for the effect 

that change in tolerance could have on our ability to compare the 

concentrations of pesticide residues relative to their tolerance in different 

years, we performed our analysis for each year using the tolerance that 

was in place for each pesticide/commodity combination in the first year of 

testing. By focusing on this common set of pesticide tolerances, our 

restricted analysis, while standardized across the years, does not include 

any changes that may have occurred in the tolerances for particular 

pesticides.

Analysis of Most Recent Unrestricted AMS Data

In the body of this report, we present our analysis of the most recent AMS 

data for the 10 selected commodities. In this analysis, we did not restrict 

the data with respect to the number of pesticides AMS tested for, the limit 

of detection it could achieve, or the EPA-established tolerance. We 
Appendix I: Objectives, Scope, and 

Methodology

Page 73 GAO-15-38 Pesticide Residue Monitoring

identified the most recent year in which AMS had sampled the 10 

commodities, and using those years’ data, we conducted the same four 

types of analysis described above (1) the number of unique detections of 

pesticide residue above the limit of detection on each sample; (2) the 

average number of pesticide residues per sample; (3) the four residues 

with the highest average residue concentration relative to that 

commodity’s pesticide tolerance; and (4) the number of presumptive 

tolerance violations. Because the AMS data were derived from a survey 

that contains sampling error, we calculated confidence intervals for each 

estimate to help us understand the reliability of these estimates.

For both the restricted and unrestricted methods of analysis, we were 

generally unable to use AMS’s data to analyze pesticide residue 

detections separately by the place of origin of the 10 commodities we 

examined. AMS’s files include data on whether the sampled commodities 

were grown domestically or imported, but there was not a sufficient and 

balanced number of both domestic and imported samples for reliable 

comparisons of the frequency or amount of residues detected. Nearly all 

sampled apples, bananas, broccoli, lettuce, and potatoes were from one 

type of origin (either imported or domestic), and green beans and pears 

had sample sizes that were larger (at least 90) in each group, but the 

differential between imported and domestic sample sizes was still of a 

magnitude greater than 4. Cantaloupe, peaches, and sweet bell peppers 

had larger numbers of both domestic and imported samples to more 

reliably analyze and report findings related to origin.

To examine limitations, if any, in AMS’s efforts to collect residue data, we 

compared the agency’s methods and its reporting of those methods with 

standards established by OMB’s Standards and Guidelines for Statistical 

Surveys as well as other best practices in survey methodology.16

 

16OMB, Standards and Guidelines for Statistical Surveys (September 2006); American 

Association for Public Opinion Research, Best Practices for Survey Research, 

In 

particular, we evaluated AMS’s survey practices for addressing 

components of coverage error, nonresponse error, and sampling error. 

We interviewed AMS officials regarding the agency’s collection and 

reporting of Pesticide Data Program data. We also interviewed (1) a 

former AMS statistician who was involved in the initial design of the 

Pesticide Data Program about the survey methodology used for gathering 

http://www.aapor.org//Best_Practices1.htm; and Federal Committee on Statistical 

Methodology, Measuring and Reporting Sources of Error in Surveys (July 2001).

Review of Methods AMS Used 

to Collect Data on Pesticide 

Residue
Appendix I: Objectives, Scope, and 

Methodology

Page 74 GAO-15-38 Pesticide Residue Monitoring

the data and (2) EPA officials in the Office of Pesticide Programs about 

their use of the AMS data and their views on the data’s reliability.

We conducted this performance audit from November 2012 to October 

2014 in accordance with generally accepted government auditing 

standards. Those standards require that we plan and perform the audit to 

obtain sufficient, appropriate evidence to provide a reasonable basis for 

our findings and conclusions based on our audit objectives. We believe 

that the evidence obtained provides a reasonable basis for our findings 

and conclusions based on our audit objectives.
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 75 GAO-15-38 Pesticide Residue Monitoring

The Food and Drug Administration (FDA) tests domestically grown and 

imported foods for pesticide residues to determine their compliance with 

pesticide tolerances established by the Environmental Protection Agency 

(EPA). When FDA tests commodities for compliance with EPA’s 

tolerances, it may find one or more violations. One type of violation 

occurs if FDA finds residue of a pesticide for which EPA has not 

established a tolerance for that commodity. Such residues are prohibited 

and constitute a violation of no tolerance. A second type of violation 

occurs if FDA finds residue that exceeds an established tolerance for that 

commodity. That is called a violation of tolerance. FDA also tests 

commodities for the residue of pesticides that are no longer registered by 

EPA for use but that may persist in the environment and for which FDA 

has established an “action level.” If FDA detects residue of an 

unregistered pesticide that exceeds an action level, according to FDA 

officials, the agency considers, on a case-by-case basis, whether the 

presence of such a residue in or on food would require an enforcement 

action to remove the food from commerce.

As discussed in this report, FDA uses targeted methods for selecting 

domestic and imported foods for pesticide residue testing rather than a 

random selection method. The agency targets foods for testing on the 

basis of a variety of factors, including the compliance history of the food, 

grower, or country of origin; the importance of the food in the U.S. diet; 

and others. Because FDA uses targeted methods, the results only 

indicate the presence or absence of violations from among the foods that 

FDA chose to sample.

In addition in this report, we examined the results of FDA’s testing of 10 

commonly consumed fruits and vegetables from 2008 through 2012. The 

10 commodities are apples, bananas, broccoli, cantaloupe, green beans, 

lettuce, peaches, pears, potatoes, and sweet bell peppers. Tables 9 

through 18 present FDA data for the 10 commodities by year from 1993 

through 2012. Specifically, the tables provide the number of samples of 

each commodity FDA tested, the number of samples FDA found to have 

at least one violation, and the number and type of violations found in each 

year.1

 

1

Data on the third type of violation—action level violations—are shown in notes to the 

tables. 

Tables 9 through 18 also indicate whether the food was of 

domestic or imported origin. Because FDA may detect multiple violations 

Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 76 GAO-15-38 Pesticide Residue Monitoring

in a single sample, the total number of violations detected may exceed 

the number of samples with one or more violations.

Table 9: Results of FDA Pesticide Residue Tolerance Compliance Testing of Apples from 1993 through 2012, by Violation 

Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 313 101 2 3 4 6 0 0 

1994 85 36 1 1 0 1 4 0 

1995 202 48 0 4 0 8 0 0 

1996 217 59 6 0 8 0 0 0 

1997 194 58 1 1 0 2 1 0 

1998 219 55 1 0 1 0 0 0 

1999 193 116 0 0 0 0 0 0 

2000 214 50 1 1 4 2 0 0 

2001 233 54 1 3 1 4 0 8 

2002 167 38 0 1 0 4 0 0 

2003 183 62 2 0 2 0 0 0 

2005 142 32 0 2 0 5 0 0 

2006 140 30 1 0 1 0 0 0 

2007 136 40 0 1 0 1 0 2 

2008 118 11 0 1 0 2 0 2 

2009 91 18 0 1 0 1 0 0 

2010 123 a 28 0 0 0 0 0 0 

2011 84 21 0 2 0 2 0 0 

2012 104 25 1 0 1 0 0 0 

Total 3,158 882 17 21 22 38 5 12

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.

a

Our analysis focuses on two types of violation; violations of no tolerance and violations of tolerance. 

FDA also may establish, as guidance, a nonbinding level, known as an action level, for an 

unavoidable residue of a cancelled pesticide that persists in the environment. FDA detected pesticide 

residues that exceeded action levels in two domestic and three imported apple samples in 2010, 

which are not shown in the table.
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 77 GAO-15-38 Pesticide Residue Monitoring

Table 10: Results of FDA Pesticide Residue Tolerance Compliance Testing of Bananas from 1993 through 2012, by Violation 

Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 6 188 0 0 0 0 0 0 

1994 2 281 0 2 0 8 0 0 

1995 31 231 0 1 0 0 0 2 

1996 9 251 0 0 0 0 0 0 

1997 7 329 0 0 0 0 0 0 

1998 5 158 0 0 0 0 0 0 

1999 3 200 0 0 0 0 0 0 

2000 2 294 0 1 0 4 0 0 

2001 0 86 0 0 0 0 0 0 

2002 0 76 0 0 0 0 0 0 

2003 2 116 0 1 0 1 0 0 

2005 1 24 0 0 0 0 0 0 

2006 2 18 0 0 0 0 0 0 

2007 0 41 0 0 0 0 0 0 

2008 0 11 0 0 0 0 0 0 

2009 1 13 0 0 0 0 0 0 

2010 0 18 0 0 0 0 0 0 

2011 0 15 0 0 0 0 0 0 

2012 1 13 0 0 0 0 0 0 

Total 72 2,363 0 5 0 13 0 2 

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 78 GAO-15-38 Pesticide Residue Monitoring

Table 11: Results of FDA Pesticide Residue Tolerance Compliance Testing of Broccoli from 1993 through 2012, by Violation 

Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 59 80 1 0 1 0 0 0 

1994 23 68 0 0 0 0 0 0 

1995 23 50 0 0 0 0 0 0 

1996 26 36 0 0 0 0 0 0 

1997 23 43 0 0 0 0 0 0 

1998 13 39 0 0 0 0 0 0 

1999 26 63 0 2 0 2 0 6 

2000 14 36 0 0 0 0 0 0 

2001 24 a 33 2 0 1 0 4 0 

2002 28 52 0 0 0 0 0 0 

2003 27 45 0 0 0 0 0 0 

2005 23 58 0 0 0 0 0 0 

2006 12 43 1 0 0 0 2 0 

2007 13 58 0 1 0 2 0 0 

2008 13 68 0 1 0 2 0 0 

2009 11 47 0 0 0 0 0 0 

2010 13 59 0 2 0 1 0 2 

2011 4 59 0 1 0 0 0 2 

2012 7 27 0 0 0 0 0 0 

Total 382 964 4 7 2 7 6 10

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.

a

Our analysis focuses on two types of violation; violations of no tolerance and violations of tolerance. 

FDA also may establish, as guidance, a nonbinding level, known as an action level, for an 

unavoidable residue of a cancelled pesticide that persists in the environment. FDA detected pesticide 

residue that exceeded an action level in one domestic sample of broccoli in 2001, which is not shown 

in the table.
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 79 GAO-15-38 Pesticide Residue Monitoring

Table 12: Results of FDA Pesticide Residue Tolerance Compliance Testing of Cantaloupe from 1993 through 2012, by 

Violation Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 53 118 0 1 0 0 0 2 

1994 64 57 0 9 0 11 0 6 

1995 45 90 1 11 2 17 0 4 

1996 75 106 3 12 7 24 0 0 

1997 64 81 1 1 1 2 0 0 

1998 26 63 0 5 0 8 0 2 

1999 41 91 0 0 0 0 0 0 

2000 18 44 0 0 0 0 0 0 

2001 21 39 0 0 0 0 0 0 

2002 22 49 0 0 0 0 0 0 

2003 22 18 0 0 0 0 0 0 

2005 44 4 0 0 0 0 0 0 

2006 4 4 0 0 0 0 0 0 

2007 18 8 1 0 3 0 0 0 

2008 3 7 0 0 0 0 0 0 

2009 17 3 0 0 0 0 0 0 

2010 6 8 0 1 0 2 0 0 

2011 4 22 0 2 0 2 0 2 

2012 16 6 0 0 0 0 0 0 

Total 563 818 6 42 13 66 0 16

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 80 GAO-15-38 Pesticide Residue Monitoring

Table 13: Results of FDA Pesticide Residue Tolerance Compliance Testing of Green Beans from 1993 through 2012, by 

Violation Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 89 72 0 10 0 21 0 6 

1994 135 100 1 15 2 28 0 4 

1995 101 103 0 13 0 29 0 4 

1996 120 60 0 3 0 7 0 0 

1997 163 91 4 12 18 26 3 4 

1998 98 144 1 14 2 34 0 2 

1999 111 100 2 11 2 24 2 2 

2000 124 73 0 10 0 25 0 0 

2001 79 57 2 3 4 2 0 10

2002 83 80 1 7 2 11 0 4 

2003 64 78 2 17 4 38 0 1 

2005 78 114 1 19 1 36 0 0 

2006 34 97 0 7 0 16 0 0 

2007 28 116 2 3 4 5 0 0 

2008 27 103 1 9 2 20 0 0 

2009 34 104 1 4 1 10 0 0 

2010 37 129 2 3 1 5 1 0 

2011 37 58 1 7 1 13 0 0 

2012 17 43 1 3 1 5 0 0 

Total 1,459 1,722 22 170 45 355 6 37

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 81 GAO-15-38 Pesticide Residue Monitoring

Table 14: Results of FDA Pesticide Residue Tolerance Compliance Testing of Lettuce from 1993 through 2012, by Violation 

Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 143 43 5 7 5 8 6 6 

1994 70 37 5 0 8 0 0 0 

1995 87 50 6 4 2 2 18 10

1996 80 45 2 1 1 2 6 0 

1997 67 a 27 1 0 1 0 0 0 

1998 31 28 0 1 0 2 0 0 

1999 35 47 0 2 0 12 0 0 

2000 34 17 0 0 0 0 0 0 

2001 23 22 0 3 0 8 0 2 

2002 19 13 0 0 0 0 0 0 

2003 49 6 3 1 5 2 0 0 

2005 44 29 1 2 1 3 0 0 

2006 38 7 1 0 4 0 0 0 

2007 36 33 2 0 0 0 4 0 

2008 54 28 1 0 1 0 0 0 

2009 73 30 2 0 2 0 0 0 

2010 35 23 0 0 0 0 0 0 

2011 7 34 0 0 0 0 0 0 

2012 3 2 0 0 0 0 0 0 

Total 928 521 29 21 30 39 34 18

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.

a

Our analysis focuses on two types of violation; violations of no tolerance and violations of tolerance. 

FDA also may establish, as guidance, a nonbinding level, known as an action level, for an 

unavoidable residue of a cancelled pesticide that persists in the environment. FDA detected pesticide 

residue that exceeded an action level in one domestic sample of lettuce in 1997, which is not shown 

in the table.
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 82 GAO-15-38 Pesticide Residue Monitoring

Table 15: Results of FDA Pesticide Residue Tolerance Compliance Testing of Peaches from 1993 through 2012, by Violation 

Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 135 63 7 0 4 0 8 0 

1994 244 80 3 3 7 10 3 0 

1995 200 52 2 2 2 6 1 0 

1996 125 41 0 3 0 7 0 0 

1997 162 33 2 1 2 2 3 0 

1998 149 46 0 1 0 0 0 2 

1999 130 27 0 0 0 0 0 0 

2000 116 44 1 2 0 4 2 0 

2001 85 26 4 1 9 1 1 0 

2002 96 a 43 2 1 1 0 0 3 

2003 95 36 2 1 3 0 0 2 

2005 80 16 2 0 0 0 8 0 

2006 52 21 1 0 0 0 2 0 

2007 36 16 1 0 1 0 0 0 

2008 29 15 0 0 0 0 0 0 

2009 35 8 0 0 0 0 0 0 

2010 44 11 6 0 5 0 2 0 

2011 20 17 2 0 2 0 0 0 

2012 24 19 1 1 1 0 1 0 

Total 1,857 614 36 16 37 30 31 7 

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.

a

Our analysis focuses on two types of violation; violations of no tolerance and violations of tolerance. 

FDA also may establish, as guidance, a nonbinding level, known as an action level, for an 

unavoidable residue of a cancelled pesticide that persists in the environment. FDA detected pesticide 

residue that exceeded an action level in one domestic sample of peaches in 2002, which is not shown 

in the table. 
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 83 GAO-15-38 Pesticide Residue Monitoring

Table 16: Results of FDA Pesticide Residue Tolerance Compliance Testing of Pears from 1993 through 2012, by Violation 

Type and Origin

Number of samples

Samples with one

or more violations

Number of violations 

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 29 89 1 8 2 14 0 2 

1994 53 106 0 20 0 35 0 4 

1995 70 65 5 1 5 2 0 0 

1996 69 61 0 1 0 0 0 2 

1997 88 88 3 0 5 0 0 0 

1998 49 44 1 0 1 0 0 0 

1999 28 73 0 0 0 0 0 0 

2000 72 63 0 0 0 0 0 0 

2001 34 92 0 11 0 34 0 3 

2002 40 45 0 2 0 2 0 0 

2003 43 48 0 4 0 4 0 0 

2005 33 34 4 1 4 2 0 0 

2006 17 16 0 1 0 2 0 0 

2007 20 28 7 4 7 7 0 0 

2008 14 18 0 0 0 0 0 0 

2009 9 8 0 0 0 0 0 0 

2010 18 13 0 0 0 0 0 0 

2011 15 18 0 5 0 5 0 0 

2012 18 a 16 1 1 3 0 0 0 

Total 719 925 22 59 27 107 0 11

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.

a

Our analysis focuses on two types of violation; violations of no tolerance and violations of tolerance. 

FDA also may establish, as guidance, a nonbinding level, known as an action level, for an 

unavoidable residue of a cancelled pesticide that persists in the environment. FDA detected two 

action level violations in imported pears in 2012, which are not shown in the table. 
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 84 GAO-15-38 Pesticide Residue Monitoring

Table 17: Results of FDA Pesticide Residue Tolerance Compliance Testing of Potatoes from 1993 through 2012, by Violation 

Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 213 49 0 0 0 0 0 0 

1994 192 26 0 0 0 0 0 0 

1995 270 23 8 0 18 0 7 0 

1996 234 78 2 0 4 0 0 0 

1997 174 a 20 2 0 0 0 0 0 

1998 142 a 26 5 4 4 8 0 0 

1999 116 a 38 3 0 3 0 0 0 

2000 102 14 2 0 4 0 0 0 

2001 142 15 6 0 0 0 12 0 

2002 124 33 0 0 0 0 0 0 

2003 98 55 1 3 2 14 0 0 

2005 124 36 0 2 0 3 0 0 

2006 88 28 0 4 0 12 0 0 

2007 79 40 0 0 0 0 0 0 

2008 82 40 0 1 0 2 0 0 

2009 43 26 0 1 0 2 0 2 

2010 76 40 3 2 1 2 11 2 

2011 46 45 0 0 0 0 0 0 

2012 56 26 0 2 0 2 0 0 

Total 2,401 658 32 19 36 45 30 4 

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.

a

Our analysis focuses on two types of violation; violations of no tolerance and violations of tolerance. 

FDA also may establish, as guidance, a nonbinding level, known as an action level, for an 

unavoidable residue of a cancelled pesticide that persists in the environment. FDA detected six action 

level violations in domestic potatoes in 1997, one in domestic potatoes in 1998, and one in domestic 

potatoes in 1999, which are not shown in the table. 
Appendix II: Food and Drug Administration 

Pesticide Residue Monitoring Data for 10 

Selected Commodities from 1993 through 2012

Page 85 GAO-15-38 Pesticide Residue Monitoring

Table 18: Results of FDA Pesticide Residue Tolerance Compliance Testing of Sweet Bell Pepper from 1993 through 2012, by 

Violation Type and Origin

Number of samples

Samples with one

or more violations

Number of violations

of no tolerance

Number of violations

of tolerance

Year Domestic Imported Domestic Imported Domestic Imported Domestic Imported

1993 48 199 0 1 0 0 0 3 

1994 43 230 1 10 0 23 2 6 

1995 40 309 0 8 0 14 0 2 

1996 80 251 0 1 0 0 0 2 

1997 85 200 0 0 0 0 0 0 

1998 29 176 0 6 0 8 0 2 

1999 37 187 0 5 0 11 0 0 

2000 21 139 0 5 0 12 0 0 

2001 14 221 0 19 0 56 0 4 

2002 14 276 0 20 0 77 0 4 

2003 32 418 0 30 0 100 0 3 

2005 47 235 0 8 0 9 0 3 

2006 15 161 0 8 0 20 0 0 

2007 12 200 2 8 4 16 0 4 

2008 12 80 0 2 0 4 0 0 

2009 19 144 0 7 0 13 0 2 

2010 12 106 0 7 0 10 0 0 

2011 21 108 0 4 0 6 0 1 

2012 11 37 0 1 0 5 0 0 

Total 592 3,677 3 150 4 384 2 36

Source: GAO analysis of FDA data. | GAO-15-38

Note: Because FDA may detect multiple violations in a single sample, the total number of violations 

detected may exceed the number of samples with one or more violations. FDA was not able to 

provide us with test results from 2004 that were comparable in detail to the other years. Therefore, we 

could not include that year in our analysis of pesticide residue test results.
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 86 GAO-15-38 Pesticide Residue Monitoring

To analyze pesticide residues in foods over time, we took into account 

changes in how agencies collected residue data and changes in pesticide 

tolerances. In this appendix, we discuss how changes in the Agricultural 

Marketing Service’s (AMS) methods of testing foods for pesticide 

residues and in the Environmental Protection Agency’s (EPA) established 

pesticide tolerances can affect the comparability of the residue data from 

AMS’s Pesticide Data Program at different points in time. In particular, we 

found that changes to the set of pesticides AMS tested for, improvements 

in AMS’s ability to detect smaller quantities of pesticide residue, and 

changes made by EPA to the established tolerance for a particular 

pesticide/commodity combination limited our ability to analyze residue 

data at different points in time.

To develop comparable measures for examining changes in residue 

detections at different points in time, we performed an analysis that 

focused on the set of pesticides; limits of detection, which is the 

concentration of a residue that AMS could detect with accuracy; and 

tolerances that were common to all years that we reviewed (1998 through 

2012) for each particular commodity. The data that AMS collected in 

recent years were generally more extensive than the data the agency 

collected in earlier years because it added pesticides to its testing 

program and lowered its limits of detection for particular pesticides. In our 

analysis, we “restricted” the data on pesticides from recent years, 

meaning that we assumed that the older methods were still in use and, 

therefore, excluded more recent data that AMS collected with new 

methods. This allowed us, for the period of our review, to make 

comparisons between data on pesticide residues, limits of detection, and 

tolerances in effect during the earlier years. However, because the data 

collected in the earlier years were generally less extensive, it was not 

possible to estimate the residues that would have been detected in earlier 

years if the list of pesticides, limits of detection, and tolerances in effect in 

recent years had been in effect in those earlier years. Therefore, our 

analysis is able to provide a comparison at different points in time for only 

the restricted set of pesticides, assuming generally higher limits of 

detection. We are unable to assess changes at different points in time for 

pesticides that were added to the list of pesticides that AMS tested for in 

recent years or for concentrations of residues only detectable with more 

sensitive testing equipment that became available in recent years.

To analyze pesticide residue data at different points in time, we selected 

the 3 most recent years of AMS data for 10 commodities; apples, 

bananas, broccoli, cantaloupe, green beans, lettuce, peaches, pears, 

Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 87 GAO-15-38 Pesticide Residue Monitoring

potatoes, and sweet bell peppers. Due to AMS’s staggered sampling 

schedule, it was not possible to select the same years for all 10 

commodities. Table 19 shows the 3 most recent years in which AMS 

tested the 10 commodities for pesticide residue, from 1998 through 2012.

Table 19: Agricultural Marketing Service (AMS) Pesticide Data Program Data 

Selected for Analysis for the Most Recent 3 Years of Testing of the Commodity 

Commodity Year 1 Year 2 Year 3

Apples 2001 2004 2010

Bananas 2002 2006 2012

Broccoli 2001 2002 2007

Cantaloupe 1999 2004 2011

Green beans 2000 2004 2008

Lettuce 2000 2005 2010

Peaches 2001 2007 2008

Pears 1998 2004 2010

Potatoes 2001 2002 2009

Sweet bell peppers 2000 2003 2010

Source: AMS. | GAO-15-38

To restrict the data set, we identified three characteristics of AMS’s 

testing that could have changed over time: (1) the list of pesticides that 

AMS tested for annually;(2) the concentration of a residue that AMS could 

detect with accuracy, or limit of detection; and (3) the tolerance 

established by EPA for a particular pesticide/commodity combination and 

against which the test results were measured to determine whether the 

residue exceeded that tolerance.

To restrict the list of pesticides, we refined the list of all pesticides for 

which AMS tested each commodity to only the pesticides that AMS tested 

that commodity for in each of the 3 years. For example, AMS tested 

apples for 93, 175, and 184 pesticides in 2001, 2004, and 2010, 

respectively. The restricted list we used for our analysis consisted of the 

83 pesticides that AMS tested apples for in each of the 3 years and, 

therefore, excluded the remaining pesticides (i.e., 10 from 2001, 92 from 

2004, and 101 from 2010).

To restrict the data with regard to limit of detection, we identified the 

highest level AMS used for a particular pesticide in the first of the 3 years 

it tested the commodity and used that value in our analyses for the 
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 88 GAO-15-38 Pesticide Residue Monitoring

second and third years of testing as well.1

To restrict the data with regard to EPA tolerances, we identified the 

tolerance for each pesticide/commodity combination in the first year and 

used that value in our analyses of the second and third years as well. For 

example, the tolerance for the pesticide methamidophos on green beans 

was 0.02 parts per million in year 2000; we used that tolerance in our 

analysis of residue data for green beans in 2004 and 2010 as well, even 

though by 2010 EPA had changed the tolerance to 3.0 parts per million. 

Restricting the tolerance only affects our analysis of the average 

concentration of residues relative to tolerance. It does not affect the 

analysis of the number of residues per sample or the average number of 

residues per sample. We note that our approach is limited by the fact that 

an EPA change to a tolerance may either increase it or decrease it. For 

the purposes of our analysis of pesticide residue concentrations as a 

percentage of tolerance over time in this appendix, we used the tolerance 

from the first year.

For example, the highest limit 

of detection for the pesticide methomyl on cantaloupe was 0.032 parts 

per million in 1999. By 2011, the highest limit of detection for methomyl

on cantaloupe had changed to 0.01 parts per million. We used the highest 

limit of detection for the methomyl/cantaloupe combination in 1999 in our 

analysis of all 3 years of restricted cantaloupe data.

2

Using the data that we restricted to account for changes in pesticides 

tested for, limits of detection, and tolerances, we examined the residue 

data for each of the 10 commodities to determine the number of residues 

AMS detected over time and the pesticide residue with the highest 

average concentration relative to that pesticide’s tolerance. For some 

commodities, there was little change in the number of detected residues 

at different points in time. For example, broccoli—one of the 10 

commodities with relatively few detections—had an average of 0.2 

pesticide residues per sample in 2001, 2002, and 2007 when the testing 

 

1

In some cases, variations in testing technology across laboratories in a given year meant 

that there were multiple limits of detection for one commodity in a year.

2

Elsewhere in this report, we presented our analysis of the pesticide with the highest 

residue concentration as a percentage of tolerance for each of the 10 select commodities 

in the most recent year of AMS testing. For that analysis, we used the tolerance as 

established for that year.

Comparison of Restricted 

AMS Data Over Time
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 89 GAO-15-38 Pesticide Residue Monitoring

methods used in 2001 were applied to those years.3

Table 20: Average Number of Pesticides Detected per Commodity Sample, Using 

Restricted Agricultural Marketing Service (AMS) Data for the Most Recent 3 Years of 

Testing

Peaches—one of the 

commodities with more detected residues—averaged 3.6 residues per 

sample in 2001, 2.2 residues per sample in 2007, and 2.1 residues per 

sample 2008 when the methods used in 2001 were applied to each year. 

For the set of pesticides and limits of detection that were common across 

the 3 years, there was little change in the number of residues detected on 

most of the 10 commodities. Table 20 presents the average number of 

pesticide residues detected per sample for all 10 commodities, using 

restricted data from the 3 most recent years of AMS testing.

Commodity Year 1 Year 2 Year 3

Apples 2.0 1.8 a 1.4 f

Bananas

k

0.4 0.3 b 0.3 g

Broccoli 

l

0.2 0.2 a 0.2 b

Cantaloupe

i

0.5 0.6 c 0.1 f

Green beans

m

1.6 1.6 d 1.2 f

Lettuce

n

0.5 0.8 d 0.5 h

Peaches

k

3.6 2.2 a 2.1 i

Pears 

l

0.8 0.5 e f 0.2

Potatoes

k

1.1 1.1 a 1.0 b

Sweet bell peppers

o

2.0 1.7 d 1.4 j

Source: GAO analysis of AMS data. | GAO-15-38

k

Note: We analyzed AMS’s data for those commodities from the 3 most recent years in which the 

agency sampled them, which are not the same for every commodity because AMS uses a staggered 

sampling schedule. We restricted the AMS data to account for changes in pesticides AMS tested for, 

the limits of detection AMS attained, and EPA-established tolerances. Averages for all years are 

based on data that have been restricted to the pesticides, limits of detection, and tolerances in effect 

during the first year. Unless otherwise indicated, all relative margins of error for 95 percent confidence 

intervals are less than plus or minus 10 percent of the value of those numerical estimates. Instances 

in which the relative margins of error are less than plus or minus 21 percent are shaded. 

a

 

3

We calculated margins of error for 95 percent confidence intervals for the AMS data and 

present them in table 20 below. However, as we described in this report, there are 

limitations in AMS’s survey methods that lead us to have some concerns about using its 

data to make national estimates about the incidence and level of pesticide residues. 

Consequently, the results of our analyses are restricted to the samples taken by AMS for 

the 10 commodities we reviewed and are not meant to be generalized to the population of 

these commodities in the food supply.

The AMS testing year was 2001.
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 90 GAO-15-38 Pesticide Residue Monitoring

b

The AMS testing year was 2002.

c

The AMS testing year was 1999.

d

The AMS testing year was 2000.

e

The AMS testing year was 1998.

f

The AMS testing year was 2004.

g

The AMS testing year was 2006.

h

The AMS testing year was 2005.

i

The AMS testing year was 2007.

j

The AMS testing year was 2003.

k

The AMS testing year was 2010.

l

The AMS testing year was 2012.

mThe AMS testing year was 2011.

n

The AMS testing year was 2008.

o

The AMS testing year was 2009.

We also analyzed the restricted AMS data to identify changes in the 

highest average concentration relative to that pesticide’s tolerance at 

different points in time. In some commodities, there was little change over 

time. For example, the pesticide that AMS detected on bananas in Year 1 

(2002) with the highest average concentration relative to its tolerance was 

imazalil at 2.4 percent relative to tolerance. We found that imazalil was 

also the pesticide with the highest average concentration relative to its 

tolerance in Year 2 (2006) at 0.9, and thiabendazole was the highest in 

Year 3 (2012) with 0.5 percent. Table 21 presents the pesticide with the 

highest average concentration relative to that pesticide’s tolerance for 

each of the 10 commodities, using restricted data from the three 3 most 

recent years of AMS testing.
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 91 GAO-15-38 Pesticide Residue Monitoring

Table 21: Pesticide Residue with the Highest Average Concentration Relative to 

That Pesticide’s Tolerance, Using Restricted Agricultural Marketing Service (AMS) 

Data

Commodity

Concentration as a

percentage of 

tolerance in Year 1

Concentration as a 

percentage of 

tolerance in Year 2

Concentration as a 

percentage of 

tolerance in Year 3

Apples 5.8% 3.7% 3.5%

Bananas 2.4% 0.9% 0.5%

Broccoli 0.1% <0.1% 0.3%

Cantaloupe 2.1% 3.2% 0.5%

Green beans 135.2% a 169.9% 137.0%

Lettuce 0.1% 11.0% 2.0%

Peaches 6.8% 7.6% 4.8%

Pears 2.3% 0.7% 0.2%

Potatoes 3.6% 4.6% 4.0%

Sweet bell peppers 2.2% 1.4% 1.5%

Source: GAO analysis of AMS data. | GAO-15-38

Note: We restricted the AMS data to account for changes in pesticides AMS tested for, the limits of 

detection AMS attained, and EPA-established tolerances. For the restricted data, all relative margins 

of error for 95 percent confidence intervals are less than plus or minus 40 percent of the value of the 

numerical estimates, with 10 exceptions. Five of the exceptions have relative margins of error that are 

less than plus or minus 86 percent and are shaded, while five have relative margins of error that are 

less than plus or minus 196 percent and are indicated in bold. For estimates with large relative 

margins of error, the particular value of the estimate should be interpreted with caution. Instead, for 

such estimates presented in this table, a more cautious interpretation is a general one: for the 

different time points we examined, the average concentration remained a small percentage of 

tolerance.

a

The pesticide AMS detected with the highest concentration relative to its tolerance in green beans 

was methamidophos. In the first testing year shown, AMS frequently detected large concentrations of 

this pesticide, including seven presumptive tolerance violations. EPA subsequently raised the 

tolerance from 0.2 parts per million to 1 part per million, but the restricted data in the table do not 

reflect that or other changes in tolerance. Therefore, with respect to green beans, the table overstates 

the highest average concentration relative to the tolerance for methamidophos in the second and third 

years of testing.

We also compared the original, or unrestricted, data to the restricted data 

to determine the effect that the changes in pesticides tested for, limits of 

detection, and EPA tolerances had on our analysis. We found the number 

of residues detected and the concentrations detected as a percentage of 

tolerance in the 3 most recent years were generally higher when using 

unrestricted data than when using restricted data. We also found that, 

regardless of whether we used unrestricted or restricted data, when 

pesticide residues were detected, they were detected at low 

concentrations relative to their established tolerances.

Comparing Unrestricted 

AMS Pesticide Residue 

Data with Restricted AMS 

Data
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 92 GAO-15-38 Pesticide Residue Monitoring

Furthermore, we found that in the unrestricted AMS data set, the number 

of residues detected per commodity was higher when compared to the 

restricted data. We compared unrestricted AMS data to restricted AMS 

data for each of the 10 selected commodities to determine the effect of 

expanded testing methods on the number of pesticides detected in the 

most recent year. Broccoli is one commodity that shows that the 

enhanced testing methods, which were used in the most recent years, 

detected significantly more residues than the earlier testing methods. 

Using the restricted data, broccoli was one of the commodities least likely 

to have residues in test results that we examined. Specifically, 14 percent 

of the 720 individual samples of broccoli AMS tested in 2001 had 

detected residues, and about 20 and 17 percent of more than 735 

samples had detected residues in 2002 and 2007, respectively.4

If AMS’s 2001 testing methods had persisted, a significant number of 

residues would not have been detected in 2007. Therefore, enhanced 

testing methods allowed for the detection of additional residues in 2007, 

but our analysis does not indicate whether these residues would have 

been detected in earlier years if these enhanced testing methods had 

been used in those years as well. Table 22 presents a comparison of 

unrestricted and restricted AMS data from the most recent year of AMS 

testing for all 10 commodities.

Using 

the restricted data, we determined that AMS detected an average of 0.2 

residues on sampled broccoli in 2001, 2002, and 2007. The results of our 

two methods of analysis for broccoli were not substantially different for 

the first 2 years; our analysis using the unrestricted AMS data found an 

average of 0.4 residues for sampled broccoli in 2001 and 2002. However, 

in 2007, the unrestricted AMS data show that broccoli samples had an 

average of 1.7 residues per sample with detected residues on more than 

88 percent of broccoli samples.

 

4

The 95 percent margin of error for percent of samples with detected residues for each 

year is within plus or minus 5 percentage points.
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 93 GAO-15-38 Pesticide Residue Monitoring

Table 22: Comparison of the Average Number of Pesticides Detected per Sample, 

Using Restricted and Unrestricted Agricultural Marketing Service (AMS) Data from 

the Most Recent Year of Testing 

Commodity Restricted data Unrestricted data

Apples 1.4 a 5.2

Bananas 0.3 b 1.3

Broccoli 0.2 c 1.7

Cantaloupe 0.1 d 0.5

Green beans 1.2 e 1.9

Lettuce 0.5 a 3.4

Peaches 2.1 e 3.5

Pears 0.2 a 1.7

Potatoes 0.9 f 1.9

Sweet bell peppers 1.4 a 4.3

Source: GAO analysis of AMS data. | GAO-15-38

Note: We restricted the AMS data to account for changes in pesticides AMS tested for, the limits of 

detection AMS attained, and EPA-established tolerances; unrestricted data do not account for those 

changes. For the restricted data, unless indicated, all relative margins of error for 95 percent 

confidence intervals are less than plus or minus 10 percent of the value of those numerical estimates. 

Five instances in which the relative margins of error are less than plus or minus 21 percent are shown 

in bold. For the unrestricted data, all relative margins of error are less than plus or minus 11 percent.

a

The AMS testing year was 2010.

b

The AMS testing year was 2012.

c

The AMS testing year was 2007.

d

The AMS testing year was 2011.

e

The AMS testing year was 2008.

f

The AMS testing year was 2009.

We also found that using unrestricted rather than restricted data produced 

somewhat different results regarding the pesticide with the highest 

average residue concentrations relative to tolerance, but that the average 

concentrations were also low relative to their established tolerances.5

 

5

We did not consider in this analysis those pesticides that AMS detected on samples of 

any of the 10 commodities but that do not have an established tolerance for that 

commodity. 

For 

example, the commodity with the pesticide with highest average 

concentration relative to its tolerance using the unrestricted data was 

potatoes, at 9.9 percent. That compared to 4.0 percent using the 

restricted data.
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 94 GAO-15-38 Pesticide Residue Monitoring

Differences in the concentrations relative to tolerance between the two 

types of data could suggest that tolerances were lowered or that the 

unrestricted data set of pesticides included pesticides with higher 

concentrations relative to tolerance in later years that were not part of the 

restricted data set. It was beyond the scope of our review to determine 

which, if any, of these scenarios occurred for each commodity. However, 

green beans provided a clear example of the effect that a change in 

tolerance could have on our analysis. In 2000, the tolerance for the 

pesticide methamidophos on green beans was 0.2 parts per million. In 

that year, AMS detected residues in about 27 percent of its green bean 

samples, with residue concentrations averaging 135 percent of the 

tolerance. Those detections included seven presumptive tolerance 

violations for that pesticide. After 2000, EPA increased the tolerance for 

methamidophos on green beans to 1 part per million. Using the restricted 

data, which assumes that the first year tolerance of 0.2 parts per million 

continues into the second and third year, AMS detected residues with 

concentrations that averaged about 170 and 137 percent of that 

tolerance, respectively. However, using unrestricted data from 2004 and 

2008 that accounted for the new tolerance of 1 part per million, we found 

that AMS detected residue concentrations averaging 3.4 percent and 0.9 

percent of the tolerance for methamidophos, respectively. Table 23 

presents the highest pesticide residue concentration as a percentage of 

tolerance in the most recent year of AMS testing for all 10 commodities 

using both unrestricted and restricted AMS data.
Appendix III: Analysis of Pesticide Residues at 

Different Points in Time, Taking into Account 

Changes in Monitoring Methodologies and 

Pesticide Tolerances

Page 95 GAO-15-38 Pesticide Residue Monitoring

Table 23: Comparison of Restricted and Unrestricted Agricultural Marketing Service 

(AMS) Data for Pesticide Residue with the Highest Average Concentration Relative 

to That Pesticide’s Tolerance for the Most Recent Year of Testing

Concentration as a percentage

of tolerance in most recent year

Commodity Using restricted data Using unrestricted data

Apples 3.5% a 5.2%

Bananas 0.5% b 0.7%

Broccoli 0.3% c 0.1%

Cantaloupe 0.5% d 0.9%

Green beans 136.8% e 2.4%

Lettuce 2.0% a 0.6%

Peaches 4.8% e 4.8%

Pears 0.2% a 2.9%

Potatoes 4.0% f 9.9%

Sweet bell peppers 1.5% a 2.8%

Source: GAO analysis of AMS data. | GAO-15-38

Note: We restricted the AMS data to account for changes in pesticides AMS tested for, the limits of 

detection AMS attained, and EPA-established tolerances; unrestricted data do not account for those 

changes. For the restricted data, all relative margins of error are less than plus or minus 40 percent of 

the numerical estimate with five exceptions that have relative margins of error that are less than plus 

or minus 196 percent and are shown in bold. For the unrestricted data, all relative margins of error 

are less than plus or minus 40 percent with two exceptions that have relative margins of error that are 

less than plus or minus 90 percent and are shown in bold. For estimates with large relative margins of 

error, the particular value of the estimate should be interpreted with caution. Instead, for such 

estimates presented in this table, a more cautious interpretation is a general one: for the different time 

points we examined, with the exception of green beans, the average concentration remained a small 

percentage of tolerance.

a

The AMS testing year was 2010.

b

The AMS testing year was 2012.

c

The AMS testing year was 2007.

d

The AMS testing year was 2011.

e

The AMS testing year was 2008.

f

The AMS testing year was 2009.
Appendix IV: Comments from the Department 

of Health and Human Services

Page 96 GAO-15-38 Pesticide Residue Monitoring

Appendix IV: Comments from the 

Department of Health and Human Services
Appendix IV: Comments from the Department 

of Health and Human Services

Page 97 GAO-15-38 Pesticide Residue Monitoring
Appendix IV: Comments from the Department 

of Health and Human Services

Page 98 GAO-15-38 Pesticide Residue Monitoring
Appendix IV: Comments from the Department 

of Health and Human Services

Page 99 GAO-15-38 Pesticide Residue Monitoring
Appendix V: Comments from the U.S. 

Department of Agriculture

Page 100 GAO-15-38 Pesticide Residue Monitoring

Appendix V: Comments from the U.S. 

Department of Agriculture
Appendix V: Comments from the U.S. 

Department of Agriculture

Page 101 GAO-15-38 Pesticide Residue Monitoring
Appendix V: Comments from the U.S. 

Department of Agriculture

Page 102 GAO-15-38 Pesticide Residue Monitoring
Appendix VI: GAO Contact and Staff 

Acknowledgments

Page 103 GAO-15-38 Pesticide Residue Monitoring

John Neumann, (202) 512-3841 or Neumannj@gao.gov

In addition to the individual named above, James R. Jones, Jr. (Assistant 

Director), Susan Baker, Kevin Bray, Mark Braza, Ross Campbell, John 

Delicath, Sheyda R. Esnaashari, Jason Trentacoste, and Sonya 

Vartivarian made key contributions to this report. Armetha Liles, Monica 

Savoy, and Kiki Theodoropoulos also made important contributions to this 

report.

Appendix VI: GAO Contact and Staff 

Acknowledgments

GAO Contact

Staff 

Acknowledgments
Related GAO Products

Page 104 GAO-15-38 Pesticide Residue Monitoring

Pesticide Safety: Improvements Needed in EPA’s Good Laboratory 

Practices Inspection Program. GAO-14-289. Washington, D.C.: May 15, 

2014.

Environmental Health: EPA Has Made Substantial Progress but Could 

Improve Processes for Considering Children’s Health. GAO-13-254. 

Washington, D.C.: August 12, 2013.

Pesticides: EPA Should Take Steps to Improve Its Oversight of 

Conditional Registrations. GAO-13-145. Washington, D.C.: August 8, 

2013.

Food Safety: FDA Can Better Oversee Food Imports by Assessing and 

Leveraging Other Countries’ Oversight Resources. GAO-12-933. 

Washington, D.C.: September 28, 2012.

Information Technology: FDA Needs to Fully Implement Key 

Management Practices to Lessen Modernization Risks. GAO-12-346. 

Washington, D.C.: March 15, 2012.

Seafood Safety: FDA Needs to Improve Oversight of Imported Seafood 

and Better Leverage Limited Resources. GAO-11-286. Washington, D.C.: 

April 14, 2011.

Agricultural Chemicals: USDA Could Enhance Pesticide and Fertilizer 

Usage Data, Improve Outreach, and Better Leverage Resources. 

GAO-11-37. Washington, D.C.: November 4, 2010.

Food and Drug Administration: Overseas Offices Have Taken Steps to 

Help Ensure Import Safety, but More Long-Term Planning Is Needed. 

GAO-10-960. Washington, D.C.: September 30, 2010.

Food Safety: FDA Could Strengthen Oversight of Imported Food by 

Improving Enforcement and Seeking Additional Authorities. 

GAO-10-699T. Washington, D.C.: May 6, 2010.

Food Safety: Agencies Need to Address Gaps in Enforcement and 

Collaboration to Enhance Safety of Imported Food. GAO-09-873. 

Washington, D.C.: September 15, 2009.

Food Safety: Improvements Needed in FDA Oversight of Fresh Produce. 

GAO-08-1047. Washington, D.C.: September 26, 2008.

Related GAO Products
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Page 105 GAO-15-38 Pesticide Residue Monitoring

Agricultural Pesticides: Management Improvements Needed to Further 

Promote Integrated Pest Management. GAO-01-815. Washington, D.C.: 

August 17, 2001.

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